Gene expression profiling of egfr positive cancer

ABSTRACT

The present invention concerns prognostic markers associated with EGFR positive cancer. In particular, the invention concerns prognostic methods based on the molecular characterization of gene expression in paraffin-embedded, fixed tissue samples of EGFR-expressing cancer, which allow a physician to predict whether a patient is likely to respond well to treatment with an EGFR inhibitor.

This application claims priority under 35 U.S.C. §119(e) to provisionalapplication Ser. No. 60/427,090 filed on Nov. 15, 2002, the entiredisclosure of which is hereby expressly incorporated by reference.

BACKGROUND OF THE INVENTION

1. Field of the Invention

The present invention concerns gene expression profiling of tissuesamples obtained from EGFR-positive cancer. More specifically, theinvention provides diagnostic, prognostic and predictive methods basedon the molecular characterization of gene expression inparaffin-embedded, fixed tissue samples of EGFR-expressing cancer, whichallow a physician to predict whether a patient is likely to respond wellto treatment with an EGFR inhibitor. In addition, the present inventionprovides treatment methods based on such findings.

2. Description of the Related Art

Oncologists have a number of treatment options available to them,including different combinations of chemotherapeutic drugs that arecharacterized as “standard of care,” and a number of drugs that do notcarry a label claim for particular cancer, but for which there isevidence of efficacy in that cancer. Best likelihood of good treatmentoutcome requires that patients be assigned to optimal available cancertreatment, and that this assignment be made as quickly as possiblefollowing diagnosis.

Currently, diagnostic tests used in clinical practice are singleanalyte, and therefore do not capture the potential value, of knowingrelationships between dozens of different markers. Moreover, diagnostictests are frequently not quantitative, relying on immunohistochemistry.This method often yields different results in different laboratories, inpart because the reagents are not standardized, and in part because theinterpretations are subjective and cannot be easily quantified.RNA-based tests have not often been used because of the problem of RNAdegradation over time and the fact that it is difficult to obtain freshtissue samples from patients for analysis. Fixed paraffin-embeddedtissue is more readily available and methods have been established todetect RNA in fixed tissue. However, these methods typically do notallow for the study of large numbers of genes (DNA or RNA) from smallamounts of material. Thus, traditionally fixed tissue has been rarelyused other than for immunohistochemistry detection of proteins.

Recently, several groups have published studies concerning theclassification of various cancer types by microarray gene expressionanalysis (see, e.g. Golub et al., Science 286:531-537 (1999);Bhattacharjae et al., Proc. Natl. Acad. Sci. USA 98:13790-13795 (2001);Chen-Hsiang et al., Bioinformatics 17 (Suppl. 1):S316-S322 (2001);Ramaswamy et al., Proc. Natl. Acad. Sci. USA 98:15149-15154 (2001)).Certain classifications of human breast cancers based on gene expressionpatterns have also been reported (Martin et al., Cancer Res.60:2232-2238 (2000); West et al., Proc. Natl. Acad. Sci. USA98:11462-11467 (2001); Sorlie et al., Proc. Natl. Acad. Sci. USA98:10869-10874 (2001); Yan et al., Cancer Res. 61:8375-8380 (2001)).However, these studies mostly focus on improving and refining thealready established classification of various types of cancer, includingbreast cancer, and generally do not link the findings to treatmentstrategies in order to improve the clinical outcome of cancer therapy.

Although modern molecular biology and biochemistry have revealed morethan 100 genes whose activities influence the behavior of tumor cells,state of their differentiation, and their sensitivity or resistance tocertain therapeutic drugs, with a few exceptions, the status of thesegenes has not been exploited for the purpose of routinely makingclinical decisions about drug treatments. One notable exception is theuse of estrogen receptor (ER) protein expression in breast carcinomas toselect patients to treatment with anti-estrogen drugs, such astamoxifen. Another exceptional example is the use of ErbB2 (Her2)protein expression in breast carcinomas to select patients with the Her2antagonist drug Herceptin® (Genentech, Inc., South San Francisco,Calif.).

Despite recent advances, the challenge of cancer treatment remains totarget specific treatment regimens to pathogenically distinct tumortypes, and ultimately personalize tumor treatment in order to optimizeoutcome. Hence, a need exists for tests that simultaneously providepredictive information about patient responses to the variety oftreatment options.

SUMMARY OF THE INVENTION

The present invention is based on findings of Phase II clinical studiesof gene expression in tissue samples obtained from EGFR-expressing headand neck cancer or colon cancer of human patients who responded well ordid not respond to (showed resistance to) treatment with EGFRinhibitors.

Based upon such findings, in one aspect the present invention concerns amethod for predicting the likelihood that a patient diagnosed with anEGFR-expressing cancer will respond to treatment with an EGFR inhibitor,comprising determining the expression level of one or more prognosticRNA transcripts or their products in a sample comprising EGFR-expressingcancer cells obtained from the patient, wherein the prognostictranscript is the transcript of one or more genes selected from thegroup consisting of: Bak; Bclx; BRAF; BRK; Cad17; CCND3; CD105; CD44s;CD82; CD9; CGA; CTSL; EGFRd27; ErbB3; EREG; GPC3; GUS; HGF; ID1; IGFBP3;ITGB3; ITGB3; p27; P53; PTPD1; RB1; RPLPO; STK15; SURV; TERC; TGFBR2;TIMP2; TITF1; XIAP; YB-1; A-Catenin; AKT1; AKT2; APC; Bax; B-Catenin;BTC; CA9; CCNA2; CCNE1; CCNE2; CD134; CD44E; CD44v3; CD44v6; CD68;CDC25B; CEACAM6; Chk2; cMet; COX2; cripto; DCR3; DIABLO; DPYD; DR5; EDN1endothelin; EGFR; EIF4E; ERBB4; ERK1; fas; FRP1; GRO1; HB-EGF; HER2;IGF1R; IRS1; ITGA3; KRT17; LAMC2; MTA1; NMYC; P14ARF; PAI1; PDGFA;PDGFB; PGK1; PLAUR; PPARG; RANBP2; RASSF1; RIZ1; SPRY2; Src; TFRC;TP53BP1; UPA; and VEGFC, wherein (a) the patient is unlikely to benefitfrom treatment with an EGFR inhibitor if the normalized levels of any ofthe following genes A-Catenin; AKT1; AKT2; APC; Bax; B-Catenin; BTC;CA9; CCNA2; CCNE1; CCNE2; CD134; CD44E; CD44v3; CD44v6; CD68; CDC25B;CEACAM6; Chk2; cMet; COX2; cripto; DCR3; DIABLO; DPYD; DR5; EDN1endothelin; EGFR; EIF4E; ERBB4; ERK1; fas; FRP1; GRO1; HB-EGF; HER2;IGF1R; IRS1; ITGA3; KRT17; LAMC2; MTA1; NMYC; P14ARF; PAIL; PDGFA;PDGFB; PGK1; PLAUR; PPARG; RANBP2; RASSF1; RIZ1; SPRY2; Src; TFRC;TP53BP1; upa; VEGFC, or their products are elevated above definedexpression thresholds, and (b) the patient is likely to benefit fromtreatment with an EGFR inhibitor if the normalized levels of any of thefollowing genes Bak; Bclx; BRAF; BRK; Cad17; CCND3; CD105; CD44s; CD82;CD9; CGA; CTSL; EGFRd27; ErbB3; EREG; GPC3; GUS; HGF; ID1; IGFBP3;ITGB3; ITGB3; p27; P53; PTPD1; RB1; RPLPO; STK15; SURV; TERC; TGFBR2;TIMP2; TITF1; XIAP; and YB-1, or their products are elevated abovedefined expression thresholds.

In another aspect, the present invention concerns a prognostic methodcomprising

(a) subjecting a sample comprising EGFR-expressing cancer cells obtainedfrom a patient to quantitative analysis of the expression level of atleast one gene selected from the group consisting of CD44v3; CD44v6;DR5; GRO1; KRT17; and LAMC2 gene or their products, and

(b) identifying the patient as likely to show resistance to treatmentwith an EGFR-inhibitor if the expression levels of such gene or genes,or their products, are elevated above a defined threshold. In aparticular embodiment, the gene is LAMC2.

In yet another aspect, the invention concerns a method for predictingthe likelihood that a patient diagnosed with an EGFR-expressing head orneck cancer will respond to treatment with an EGFR inhibitor, comprisingdetermining the expression level of one or more prognostic RNAtranscripts or their products in a sample comprising EGFR-expressingcancer cells obtained from such patient, wherein the prognostictranscript is the transcript of one or more genes selected from thegroup consisting of: CD44s; CD82; CGA; CTSL; EGFRd27; IGFBP3; p27; P53;RB1; TIMP2; YB-1; A-Catenin; AKT1; AKT2; APC; Bax; B-Catenin; BTC;CCNA2; CCNE1; CCNE2; CD105; CD44v3; CD44v6; CD68; CEACAM6; Chk2; cMet;COX2; cripto; DCR3; DIABLO; DPYD; DR5; EDN1 endothelin; EGFR; EIF4E;ERBB4; ERK1; fas; FRP1; GRO1; HB-EGF; HER2; IGF1R; IRS1; ITGA3; KRT17;LAMC2; MTA1; NMYC; PAIL; PDGFA; PGK1; PTPD1; RANBP2; SPRY2; TP53BP1; andVEGFC, wherein (a) normalized expression of one or more of A-Catenin;AKT1; AKT2; APC; Bax; B-Catenin; BTC; CCNA2; CCNE1; CCNE2; CD105;CD44v3; CD44v6; CD68; CEACAM6; Chk2; cMet; COX2; cripto; DCR3; DIABLO;DPYD; DR5; EDN1 endothelin; EGFR; EIF4E; ERBB4; ERK1; fas; FRP1; GR01;HB-EGF; HER2; IGF1R; IRS1; ITGA3; KRT17; LAMC2; MTA1; NMYC; PAIL; PDGFA;PGK1; PTPD1; RANBP2; SPRY2; TP53BP1; VEGFC, or the corresponding geneproduct, above determined expression thresholds indicates that thepatient is likely to show resistance to treatment with an EGFRinhibitor, and (b) normalized expression of one or more of CD44s; CD82;CGA; CTSL; EGFRd27; IGFBP3; p27; P53; RB1; TIMP2; YB-1, or thecorresponding gene product, above defined expression thresholdsindicates that the patient is likely to respond well to treatment withan EGFR inhibitor.

In a further aspect, the invention concerns a method for predicting thelikelihood that a patient diagnosed with an EGFR-expressing colon cancerwill respond to treatment with an EGFR inhibitor, comprising determiningthe expression level of one or more prognostic RNA transcripts or theirproducts in a sample comprising EGFR-expressing cancer cells obtainedfrom the patient, wherein the prognostic transcript is the transcript ofone or more genes selected from the group consisting of Bak; Bclx; BRAF;BRK; Cad17; CCND3; CCNE1; CCNE2; CD105; CD9; COX2; DIABLO; ErbB3; EREG;FRP1; GPC3; GUS; HER2; HGF; ID1; ITGB3; PTPD1; RPLPO; STK15; SURV; TERC;TGFBR2; TITF1; XIAP; CA9; CD134; CD44E; CD44v3; CD44v6; CDC25B; CGA;DR5; GR01; KRT17; LAMC2; P14ARF; PDGFB; PLAUR; PPARG; RASSF1; RIZ1; Src;TFRC; and UPA, wherein (a) elevated expression of one or more of CA9;CD134; CD44E; CD44v3; CD44v6; CDC25B; CGA; DR5; GRO1; KRT17; LAMC2;P14ARF; PDGFB; PLAUR; PPARG; RASSF1; RIZ1; Src; TFRC; and UPA, or thecorresponding gene product, above defined expression thresholdsindicates that the patient is likely to show resistance to treatmentwith an EGFR inhibitor, and normalized expression of one or more of Bak;Bclx; BRAF; BRK; Cad17; CCND3; CCNE1; CCNE2; CD105; CD9; COX2; DIABLO;ErbB3; EREG; FRP1; GPC3; GUS; HER2; HGF; ID1; ITGB3; PTPD1; RPLPO;STK15; SURV; TERC; TGFBR2; TITF1; XIAP, or the corresponding geneproduct, above certain expression thresholds indicates that the patientis likely to respond well to treatment with an EGFR inhibitor.

In another aspect, the invention concerns a method comprising treating apatient diagnosed with an EGFR-expressing cancer and determined to haveelevated normalized levels of one or more of the RNA transcripts of Bak;Bclx; BRAF; BRK; Cad17; CCND3; CD105; CD44s; CD82; CD9; CGA; CTSL;EGFRd27; ErbB3; EREG; GPC3; GUS; HGF; ID1; IGFBP3; ITGB3; ITGB3; p27;P53; PTPD1; RB1; RPLPO; STK15; SURV; TERC; TGFBR2; TEMP2; TITF1; XIAP;YB-1; A-Catenin; AKT1; AKT2; APC; Bax; B-Catenin; BTC; CA9; CCNA2;CCNE1; CCNE2; CD134; CD44E; CD44v3; CD44v6; CD68; CDC25B; CEACAM6; Chk2;cMet; COX2; cripto; DCR3; DIABLO; DPYD; DR5; EDN1 endothelin; EGFR;EIF4E; ERBB4; ERK1; fas; FRP1; GRO1; HB-EGF; HER2; IGF1R; IRS1; ITGA3;KRT17; LAMC2; MTA1; NMYC; P14ARF; PAI1; PDGFA; PDGFB; PGK1; PLAUR;PPARG; RANBP2; RASSF1; RIZ1; SPRY2; Src; TFRC; TP53BP1; UPA; and VEGFCgenes, or the corresponding gene products in the cancer, with aneffective amount of an EGFR-inhibitor, wherein elevated RNA transcriptlevel is defined by a defined expression threshold.

In yet another aspect, the invention concerns a method comprisingtreating a patient diagnosed with an EGFR-expressing head or neck cancerand determined to have elevated normalized expression of one or more ofthe RNA transcripts of CD44s; CD82; CGA; CTSL; EGFRd27; IGFBP3; p27;P53; RB1; TIMP2; YB-1; A-Catenin; AKT1; AKT2; APC; Bax; B-Catenin; BTC;CCNA2; CCNE1; CCNE2; CD105; CD44v3; CD44v6; CD68; CEACAM6; Chk2; cMet;COX2; cripto; DCR3; DIABLO; DPYD; DR5; EDN1 endothelin; EGFR; EIF4E;ERBB4; ERK1; fas; FRP1; GRO1; HB-EGF; HER2; IGF1R; IRS1; ITGA3; KRT17;LAMC2; MTA1; NMYC; PAI1; PDGFA; PGK1; PTPD1; RANBP2; SPRY2; TP53BP1;VEGFC genes, or the corresponding gene products in said cancer, with aneffective amount of an EGFR-inhibitor, wherein elevated normalized RNAtranscript level is defined by a defined expression threshold.

In a further aspect, the invention concerns a method comprising treatinga patient diagnosed with an EGFR-expressing colon cancer and determinedto have elevated normalized expression of one or more of the RNAtranscripts of Bak; Bclx; BRAF; BRK; Cad17; CCND3; CCNE1; CCNE2; CD105;CD9; COX2; DIABLO; ErbB3; EREG; FRP1; GPC3; GUS; HER2; HGF; ID1; ITGB3;PTPD1; RPLPO; STK15; SURV; TERC; TGFBR2; TITF1; XIAP; CA9; CD134; CD44E;CD44v3; CD44v6; CDC25B; CGA; DR5; GR01; KRT17; LAMC2; P14ARF; PDGFB;PLAUR; PPARG; RASSF1; RIZ1; Src; TFRC; UPA genes, or the correspondinggene products in such cancer, with an effective amount of anEGFR-inhibitor, wherein elevated normalized RNA transcript level isdefined by a defined expression threshold.

The invention further concerns an array comprising (a) polynucleotideshybridizing to the following genes: Bak; Bclx; BRAF; BRK; Cad17; CCND3;CD105; CD44s; CD82; CD9; CGA; CTSL; EGFRd27; ErbB3; EREG; GPC3; GUS;HGF; ID1; IGFBP3; ITGB3; ITGB3; p27; P53; PTPD1; RB1; RPLPO; STK15;SURV; TERC; TGFBR2; TIMP2; TITF1; XIAP; YB-1; A-Catenin; AKT1; AKT2;APC; Bax; B-Catenin; BTC; CA9; CCNA2; CCNE1; CCNE2; CD134; CD44E;CD44v3; CD44v6; CD68; CDC25B; CEACAM6; Chk2; cMet; COX2; cripto; DCR3;DIABLO; DPYD; DR5; EDN1 endothelin; EGFR; EIF4E; ERBB4; ERK1; fas; FRP1;GRO1; HB-EGF; HERZ; IGF1R; IRS1; ITGA3; KRT17; LAMC2; MTA1; NMYC;P14ARF; PAI1; PDGFA; PDGFB; PGK1; PLAUR; PPARG; RANBP2; RASSF1; RIZ1;SPRY2; Src; TFRC; TP53BP1; UPA; VEGFC; or (b) an array comprisingpolynucleotides hybridizing to the following genes: CD44v3; CD44v6; DR5;GRO1; KRT17; and LAMC2, immobilized on a solid surface; or (c) an arraycomprising polynucleotides hybridizing to the following genes: CD44s;CD82; CGA; CTSL; EGFRd27; IGFBP3; p27; P53; RB1; TIMP2; YB-1; A-Catenin;AKT1; AKT2; APC; Bax; B-Catenin; BTC; CCNA2; CCNE1; CCNE2; CD105;CD44v3; CD44v6; CD68; CEACAM6; Chk2; cMet; COX2; cripto; DCR3; DIABLO;DPYD; DR5; EDN1 endothelin; EGFR; EIF4E; ERBB4; ERK1; fas; FRP1; GRO1;HB-EGF; HER2; IGF1R; IRS1; ITGA3; KRT17; LAMC2; MTA1; NMYC; PAI1; PDGFA;PGK1; PTPD1; RANBP2; SPRY2; TP53BP1; and VEGFC, immobilized on a solidsurface, or (d) an array comprising polynucleotides hybridizing to thefollowing genes: Bak; Bclx; BRAF; BRK; Cad17; CCND3; CCNE1; CCNE2;CD105; CD9; COX2; DIABLO; ErbB3; EREG; FRP1; GPC3; GUS; HER2; HGF; ID1;ITGB3; PTPD1; RPLPO; STK15; SURV; TERC; TGFBR2; TITF1; XIAP; CA9; CD134;CD44E; CD44v3; CD44v6; CDC25B; CGA; DR5; GRO1; KRT17; LAMC2; P14ARF;PDGFB; PLAUR; PPARG; RASSF1; RIZ1; Src; TFRC; and UPA, immobilized on asolid surface.

In a further aspect, the invention concerns a method in which RNA isisolated from a fixed, paraffin-embedded tissue specimen by a procedurecomprising:

(a) incubating a section of the fixed, paraffin-embedded tissue specimenat a temperature of about 56° C. to 70° C. in a lysis buffer, in thepresence of a protease, without prior dewaxing, to form a lysissolution;

(b) cooling the lysis solution to a temperature where the waxsolidifies; and

(c) isolating the nucleic acid from the lysis solution.

In a different aspect, the invention concerns a kit comprising one ormore of (1) extraction buffer/reagents and protocol; (2) reversetranscription buffer/reagents and protocol; and (3) qPCR buffer/reagentsand protocol suitable for performing the gene expression analysismethods of the invention.

In a further aspect, the invention concerns a method for measuringlevels of mRNA products of genes listed in Tables 5A and 5B byquantitative RT-PCR (qRT-PCR) reaction, by using an amplicon listed inTables 5A and 5B and a corresponding primer-probe set listed in Tables6A-6F.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a chart illustrating the overall workflow of the process ofthe invention for measurement of gene expression. In the Figure, FPETstands for “fixed paraffin-embedded tissue,” and “RT-PCR” stands for“reverse transcriptase PCR.” RNA concentration is determined by usingthe commercial RiboGreen™ RNA Quantitation Reagent and Protocol.

FIG. 2 is a flow chart showing the steps of an RNA extraction methodaccording to the invention alongside a flow chart of a representativecommercial method.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENT A. Definitions

Unless defined otherwise, technical and scientific terms used hereinhave the same meaning as commonly understood by one of ordinary skill inthe art to which this invention belongs. Singleton et al., Dictionary ofMicrobiology and Molecular Biology 2nd ed., J. Wiley & Sons (New York,N.Y. 1994), and March, Advanced Organic Chemistry Reactions, Mechanismsand Structure 4th ed., John Wiley & Sons (New York, N.Y. 1992), provideone skilled in the art with a general guide to many of the terms used inthe present application.

One skilled in the art will recognize many methods and materials similaror equivalent to those described herein, which could be used in thepractice of the present invention. Indeed, the present invention is inno way limited to the methods and materials described. For purposes ofthe present invention, the following terms are defined below.

The term “micro array” refers to an ordered arrangement of hybridizablearray elements, preferably polynucleotide probes, on a substrate.

The term “polynucleotide,” when used in singular or plural, generallyrefers to any polyribonucleotide or polydeoxribonucleotide, which may beunmodified RNA or DNA or modified RNA or DNA. Thus, for instance,polynucleotides as defined herein include, without limitation, single-and double-stranded DNA, DNA including single- and double-strandedregions, single- and double-stranded RNA, and RNA including single- anddouble-stranded regions, hybrid molecules comprising DNA and RNA thatmay be single-stranded or, more typically, double-stranded or includesingle- and double-stranded regions. In addition, the term“polynucleotide” as used herein refers to triple-stranded regionscomprising RNA or DNA or both RNA and DNA. The strands in such regionsmay be from the same molecule or from different molecules. The regionsmay include all of one or more of the molecules, but more typicallyinvolve only a region of some of the molecules. One of the molecules ofa triple-helical region often is an oligonucleotide. The term“polynucleotide” specifically includes cDNAs. The term includes DNAs(including cDNAs) and RNAs that contain one or more modified bases.Thus, DNAs or RNAs with backbones modified for stability or for otherreasons are “polynucleotides” as that term is intended herein. Moreover,DNAs or RNAs comprising unusual bases, such as inosine, or modifiedbases, such as tritiated bases, are included within the term“polynucleotides” as defined herein. In general, the term“polynucleotide” embraces all chemically, enzymatically and/ormetabolically modified forms of unmodified polynucleotides, as well asthe chemical forms of DNA and RNA characteristic of viruses and cells,including simple and complex cells.

The term “oligonucleotide” refers to a relatively short polynucleotide,including, without limitation, single-stranded deoxyribonucleotides,single- or double-stranded ribonucleotides, RNA:DNA hybrids anddouble-stranded DNAs. Oligonucleotides, such as single-stranded DNAprobe oligonucleotides, are often synthesized by chemical methods, forexample using automated oligonucleotide synthesizers that arecommercially available. However, oligonucleotides can be made by avariety of other methods, including in vitro recombinant DNA-mediatedtechniques and by expression of DNAs in cells and organisms.

The terms “differentially expressed gene,” “differential geneexpression” and their synonyms, which are used interchangeably, refer toa gene whose expression is activated to a higher or lower level in asubject suffering from a disease, specifically cancer, such as breastcancer, relative to its expression in a normal or control subject. Theterms also include genes whose expression is activated to a higher orlower level at different stages of the same disease. It is alsounderstood that a differentially expressed gene may be either activatedor inhibited at the nucleic acid level or protein level, or may besubject to alternative splicing to result in a different polypeptideproduct. Such differences may be evidenced by a change in mRNA levels,surface expression, secretion or other partitioning of a polypeptide,for example. Differential gene expression may include a comparison ofexpression between two or more genes or their gene products, or acomparison of the ratios of the expression between two or more genes ortheir gene products, or even a comparison of two differently processedproducts of the same gene, which differ between normal subjects andsubjects suffering from a disease, specifically cancer, or betweenvarious stages of the same disease. Differential expression includesboth quantitative, as well as qualitative, differences in the temporalor cellular expression pattern in a gene or its expression productsamong, for example, normal and diseased cells, or among cells which haveundergone different disease events or disease stages. For the purpose ofthis invention, “differential gene expression” is considered to bepresent when there is at least an about two-fold, preferably at leastabout four-fold, more preferably at least about six-fold, mostpreferably at least about ten-fold difference between the expression ofa given gene in normal and diseased subjects, or in various stages ofdisease development in a diseased subject.

The term “normalized” with regard to a gene transcript or a geneexpression product refers to the level of the transcript or geneexpression product relative to the mean levels of transcripts/productsof a set of reference genes, wherein the reference genes are eitherselected based on their minimal variation across, patients, tissues ortreatments (“housekeeping genes”), or the reference genes are thetotality of tested genes. In the latter case, which is commonly referredto as “global normalization”, it is important that the total number oftested genes be relatively large, preferably greater than 50.Specifically, the term ‘normalized’ with respect to an RNA transcriptrefers to the transcript level relative to the mean of transcript levelsof a set of reference genes. More specifically, the mean level of an RNAtranscript as measured by TaqMan® RT-PCR refers to the Ct value minusthe mean Ct values of a set of reference gene transcripts.

The terms “expression threshold,” and “defined expression threshold” areused interchangeably and refer to the level of a gene or gene product inquestion above which the gene or gene product serves as a predictivemarker for patient response or resistance to a drug, in the present casean EGFR inhibitor drug. The threshold is defined experimentally fromclinical studies such as those described in examples 1 and 2, below. Theexpression threshold can be selected either for maximum sensitivity (forexample, to detect all responders to a drug), or for maximum selectivity(for example to detect only responders to a drug), or for minimum error.

The phrase “gene amplification” refers to a process by which multiplecopies of a gene or gene fragment are formed in a particular cell orcell line. The duplicated region (a stretch of amplified DNA) is oftenreferred to as “amplicon.” Usually, the amount of the messenger RNA(mRNA) produced, i.e., the level of gene expression, also increases inthe proportion of the number of copies made of the particular geneexpressed.

The term “diagnosis” is used herein to refer to the identification of amolecular or pathological state, disease or condition, such as theidentification of a molecular subtype of head and neck cancer, coloncancer, or other type of cancer. The term “prognosis” is used herein torefer to the prediction of the likelihood of cancer-attributable deathor progression, including recurrence, metastatic spread, and drugresistance, of a neoplastic disease, such as breast cancer, or head andneck cancer. The term “prediction” is used herein to refer to thelikelihood that a patient will respond either favorably or unfavorablyto a drug or set of drugs, and also the extent of those responses, orthat a patient will survive, following surgical removal or the primarytumor and/or chemotherapy for a certain period of time without cancerrecurrence. The predictive methods of the present invention can be usedclinically to make treatment decisions by choosing the most appropriatetreatment modalities for any particular patient. The predictive methodsof the present invention are valuable tools in predicting if a patientis likely to respond favorably to a treatment regimen, such as surgicalintervention, chemotherapy with a given drug or drug combination, and/orradiation therapy, or whether long-term survival of the patient,following surgery and/or termination of chemotherapy or other treatmentmodalities is likely.

The term “long-term” survival is used herein to refer to survival for atleast 5 years, more preferably for at least 8 years, most preferably forat least 10 years following surgery or other treatment.

The term “increased resistance” to a particular drug or treatmentoption, when used in accordance with the present invention, meansdecreased response to a standard dose of the drug or to a standardtreatment protocol.

The term “decreased sensitivity” to a particular drug or treatmentoption, when used in accordance with the present invention, meansdecreased response to a standard dose of the drug or to a standardtreatment protocol, where decreased response can be compensated for (atleast partially) by increasing the dose of drug, or the intensity oftreatment.

“Patient response” can be assessed using any endpoint indicating abenefit to the patient, including, without limitation, (1) inhibition,to some extent, of tumor growth, including slowing down and completegrowth arrest; (2) reduction in the number of tumor cells; (3) reductionin tumor size; (4) inhibition (i.e., reduction, slowing down or completestopping) of tumor cell infiltration into adjacent peripheral organsand/or tissues; (5) inhibition (i.e. reduction, slowing down or completestopping) of metastasis; (6) enhancement of anti-tumor immune response,which may, but does not have to, result in the regression or rejectionof the tumor; (7) relief, to some extent, of one or more symptomsassociated with the tumor; (8) increase in the length of survivalfollowing treatment; and/or (9) decreased mortality at a given point oftime following treatment.

The term “treatment” refers to both therapeutic treatment andprophylactic or preventative measures, wherein the object is to preventor slow down (lessen) the targeted pathologic condition or disorder.Those in need of treatment include those already with the disorder aswell as those prone to have the disorder or those in whom the disorderis to be prevented. In tumor (e.g., cancer) treatment, a therapeuticagent may directly decrease the pathology of tumor cells, or render thetumor cells more susceptible to treatment by other therapeutic agents,e.g., radiation and/or chemotherapy.

The term “tumor,” as used herein, refers to all neoplastic cell growthand proliferation, whether malignant or benign, and all pre-cancerousand cancerous cells and tissues.

The terms “cancer” and “cancerous” refer to or describe thephysiological condition in mammals that is typically characterized byunregulated cell growth. Examples of cancer include but are not limitedto, breast cancer, colon cancer, lung cancer, prostate cancer,hepatocellular cancer, gastric cancer, pancreatic cancer, cervicalcancer, ovarian cancer, liver cancer, bladder cancer, cancer of theurinary tract, thyroid cancer, renal cancer, carcinoma, melanoma, headand neck cancer, and brain cancer.

The “pathology” of cancer includes all phenomena that compromise thewell-being of the patient. This includes, without limitation, abnormalor uncontrollable cell growth, metastasis, interference with the normalfunctioning of neighboring cells, release of cytokines or othersecretory products at abnormal levels, suppression or aggravation ofinflammatory or immunological response, neoplasia, premalignancy,malignancy, invasion of surrounding or distant tissues or organs, suchas lymph nodes, etc.

The term “EGFR inhibitor” as used herein refers to a molecule having theability to inhibit a biological function of a native epidermal growthfactor receptor (EGFR). Accordingly, the term “inhibitor” is defined inthe context of the biological role of EGFR. While preferred inhibitorsherein specifically interact with (e.g. bind to) an EGFR, molecules thatinhibit an EGFR biological activity by interacting with other members ofthe EGFR signal transduction pathway are also specifically includedwithin this definition. A preferred EGFR biological activity inhibitedby an EGFR inhibitor is associated with the development, growth, orspread of a tumor.

The term “housekeeping gene” refers to a group of genes that codes forproteins whose activities are essential for the maintenance of cellfunction. These genes are typically similarly expressed in all celltypes. Housekeeping genes include, without limitation,glyceraldehyde-3-phosphate dehydrogenase (GAPDH), Cyp1, albumin, actins,e.g. β-actin, tubulins, cyclophilin, hypoxantinephsophoribosyltransferase (HRPT), L32. 28S, and 18S.

B. Detailed Description

The practice of the present invention will employ, unless otherwiseindicated, conventional techniques of molecular biology (includingrecombinant techniques), microbiology, cell biology, and biochemistry,which are within the skill of the art. Such techniques are explainedfully in the literature, such as, “Molecular Cloning: A LaboratoryManual”, 2^(nd) edition (Sambrook et al., 1989); “OligonucleotideSynthesis” (M. J. Gait, ed., 1984); “Animal Cell Culture” (R. I.Freshney, ed., 1987); “Methods in Enzymology” (Academic Press, Inc.);“Handbook of Experimental Immunology”, 4^(th) edition (D. M. Weir & C.C. Blackwell, eds., Blackwell Science Inc., 1987); “Gene TransferVectors for Mammalian Cells” (J. M. Miller & M. P. Calos, eds., 1987);“Current Protocols in Molecular Biology” (F. M. Ausubel et al., eds.,1987); and “PCR: The Polymerase Chain Reaction”, (Mullis et al., eds.,1994).

1. Gene Expression Profiling

In general, methods of gene expression profiling can be divided into twolarge groups: methods based on hybridization analysis ofpolynucleotides, and methods based on sequencing of polynucleotides. Themost commonly used methods known in the art for the quantification ofmRNA expression in a sample include northern blotting and in situhybridization (Parker & Barnes, Methods in Molecular Biology 106:247-283(1999)); RNAse protection assays (Hod, Biotechniques 13:852-854 (1992));and reverse transcription polymerase chain reaction (RT-PCR) (Weis etal., Trends in Genetics 8:263-264 (1992)). Alternatively, antibodies maybe employed that can recognize specific duplexes, including DNAduplexes, RNA duplexes, and DNA-RNA hybrid duplexes or DNA-proteinduplexes. Representative methods for sequencing-based gene expressionanalysis include Serial Analysis of Gene Expression (SAGE), and geneexpression analysis by massively parallel signature sequencing (MPSS).

2. Reverse Transcriptase PCR (RT-PCR)

Of the techniques listed above, the most sensitive and most flexiblequantitative method is RT-PCR, which can be used to compare mRNA levelsin different sample populations, in normal and tumor tissues, with orwithout drug treatment, to characterize patterns of gene expression, todiscriminate between closely related mRNAs, and to analyze RNAstructure.

The first step is the isolation of mRNA from a target sample. Thestarting material is typically total RNA isolated from human tumors ortumor cell lines, and corresponding normal tissues or cell lines,respectively. Thus RNA can be isolated from a variety of primary tumors,including breast, lung, colon, prostate, brain, liver, kidney, pancreas,spleen, thymus, testis, ovary, uterus, head and neck, etc., tumor, ortumor cell lines, with pooled DNA from healthy donors. If the source ofmRNA is a primary tumor, mRNA can be extracted, for example, from frozenor archived paraffin-embedded and fixed (e.g. formalin-fixed) tissuesamples.

General methods for mRNA extraction are well known in the art and aredisclosed in standard textbooks of molecular biology, including Ausubelet al., Current Protocols of Molecular Biology, John Wiley and Sons(1997). Methods for RNA extraction from paraffin embedded tissues aredisclosed, for example, in Rupp and Locker, Lab Invest. 56:A67 (1987),and De Andres et al., BioTechniques 18:42044 (1995). In particular, RNAisolation can be performed using purification kit, buffer set andprotease from commercial manufacturers, such as Qiagen, according to themanufacturer's instructions. For example, total RNA from cells inculture can be isolated using Qiagen RNeasy mini-columns. Othercommercially available RNA isolation kits include MasterPure™ CompleteDNA and RNA Purification Kit (EPICENTRE®, Madison, Wis.); and ParaffinBlock RNA Isolation Kit (Ambion, Inc.). Total RNA from tissue samplescan be isolated using RNA Stat-60 (Tel-Test). RNA prepared from tumorcan be isolated, for example, by cesium chloride density gradientcentrifugation.

As RNA cannot serve as a template for PCR, the first step in geneexpression profiling by RT-PCR is the reverse transcription of the RNAtemplate into cDNA, followed by its exponential amplification in a PCRreaction. The two most commonly used reverse transcriptases are avilomyeloblastosis virus reverse transcriptase (AMV-RT) and Moloney murineleukemia virus reverse transcriptase (MMLV-RT). The reversetranscription step is typically primed using specific primers, randomhexamers, or oligo-dT primers, depending on the circumstances and thegoal of expression profiling. For example, extracted RNA can bereverse-transcribed using a GeneAmp RNA PCR kit (Perkin Elmer, Calif.,USA), following the manufacturer's instructions. The derived cDNA canthen be used as a template in the subsequent PCR reaction.

Although the PCR step can use a variety of thermostable DNA-dependentDNA polymerases, it typically employs the Taq DNA polymerase, which hasa 5′-3′ nuclease activity but lacks a 3′-5′ proofreading endonucleaseactivity. Thus, TaqMan® PCR typically utilizes the 5′-nuclease activityof Taq or Tth polymerase to hydrolyze a hybridization probe bound to itstarget amplicon, but any enzyme with equivalent 5′ nuclease activity canbe used. Two oligonucleotide primers are used to generate an amplicontypical of a PCR reaction. A third oligonucleotide, or probe, isdesigned to detect nucleotide sequence located between the two PCRprimers. The probe is non-extendible by Taq DNA polymerase enzyme, andis labeled with a reporter fluorescent dye and a quencher fluorescentdye. Any laser-induced emission from the reporter dye is quenched by thequenching dye when the two dyes are located close together as they areon the probe. During the amplification reaction, the Taq DNA polymeraseenzyme cleaves the probe in a template-dependent manner. The resultantprobe fragments disassociate in solution, and signal from the releasedreporter dye is free from the quenching effect of the secondfluorophore. One molecule of reporter dye is liberated for each newmolecule synthesized, and detection of the unquenched reporter dyeprovides the basis for quantitative interpretation of the data.

TaqMan® RT-PCR can be performed using commercially available equipment,such as, for example, ABI PRISM 7700™ Sequence Detection System™(Perkin-Elmer-Applied Biosystems, Foster City, Calif., USA), orLightcycler (Roche Molecular Biochemicals, Mannheim, Germany). In apreferred embodiment, the 5′ nuclease procedure is run on a real-timequantitative PCR device such as the ABI PRISM 7700™ Sequence DetectionSystem™. The system consists of a thermocycler, laser, charge-coupleddevice (CCD), camera and computer. The system amplifies samples in a96-well format on a thermocycler. During amplification, laser-inducedfluorescent signal is collected in real-time through fiber optics cablesfor all 96 wells, and detected at the CCD. The system includes softwarefor running the instrument and for analyzing the data.

5′-Nuclease assay data are initially expressed as Ct, or the thresholdcycle. As discussed above, fluorescence values are recorded during everycycle and represent the amount of product amplified to that point in theamplification reaction. The point when the fluorescent signal is firstrecorded as statistically significant is the threshold cycle (C_(t)).

To minimize errors and the effect of sample-to-sample variation, RT-PCRis usually performed using an internal standard. The ideal internalstandard is expressed at a constant level among different tissues, andis unaffected by the experimental treatment. RNAs most frequently usedto normalize patterns of gene expression are mRNAs for the housekeepinggenes glyceraldehyde-3-phosphate-dehydrogenase (GAPDH) and 13-actin.

A more recent variation of the RT-PCR technique is the real timequantitative PCR, which measures PCR product accumulation through adual-labeled fluorigenic probe (i.e., TaqMan® probe). Real time PCR iscompatible both with quantitative competitive PCR, where internalcompetitor for each target sequence is used for normalization, and withquantitative comparative PCR using a normalization gene contained withinthe sample, or a housekeeping gene for RT-PCR. For further details see,e.g. Held et al., Genome Research 6:986-994 (1996).

According to one aspect of the present invention, PCR primers and probesare designed based upon intron sequences present in the gene to beamplified. In this embodiment, the first step in the primer/probe designis the delineation of intron sequences within the genes. This can bedone by publicly available software, such as the DNA BLAT softwaredeveloped by Kent, W. J., Genome Res. 12(4):656-64 (2002), or by theBLAST software including its variations. Subsequent steps follow wellestablished methods of PCR primer and probe design.

In order to avoid non-specific signals, it is important to maskrepetitive sequences within the introns when designing the primers andprobes. This can be easily accomplished by using the Repeat Maskerprogram available on-line through the Baylor College of Medicine, whichscreens DNA sequences against a library of repetitive elements andreturns a query sequence in which the repetitive elements are masked.The masked intron sequences can then be used to design primer and probesequences using any commercially or otherwise publicly availableprimer/probe design packages, such as Primer Express (AppliedBiosystems); MGB assay-by-design (Applied Biosystems); Primer3 (SteveRozen and Helen J. Skaletsky (2000) Primer3 on the WWW for general usersand for biologist programmers. In: Krawetz S, Misener S (eds)Bioinformatics Methods and Protocols: Methods in Molecular Biology.Humana Press, Totowa, N.J., pp 365-386)

The most important factors considered in PCR primer design includeprimer length, melting temperature (Tm), and G/C content, specificity,complementary primer sequences, and 3′-end sequence. In general, optimalPCR primers are generally 17-30 bases in length, and contain about20-80%, such as, for example, about 50-60% G+C bases. Tm's between 50and 80° C., e.g. about 50 to 70° C. are typically preferred.

For further guidelines for PCR primer and probe design see, e.g.Dieffenbach, C. W. et al., “General Concepts for PCR Primer Design” in:PCR Primer, A Laboratory Manual, Cold Spring Harbor Laboratory Press,New York, 1995, pp. 133-155; Innis and Gelfand, “Optimization of PCRs”in: PCR Protocols, A Guide to Methods and Applications, CRC Press,London, 1994, pp. 5-11; and Plasterer, T. N. Primerselect: Primer andprobe design. Methods Mol. Biol. 70:520-527 (1997), the entiredisclosures of which are hereby expressly incorporated by reference.

3. Microarrays

Differential gene expression can also be identified, or confirmed usingthe microarray technique. Thus, the expression profile of breastcancer-associated genes can be measured in either fresh orparaffin-embedded tumor tissue, using microarray technology. In thismethod, polynucleotide sequences of interest (including cDNAs andoligonucleotides) are plated, or arrayed, on a microchip substrate. Thearrayed sequences are then hybridized with specific DNA probes fromcells or tissues of interest. Just as in the RT-PCR method, the sourceof mRNA typically is total RNA isolated from human tumors or tumor celllines, and corresponding normal tissues or cell lines. Thus RNA can beisolated from a variety of primary tumors or tumor cell lines. If thesource of mRNA is a primary tumor, mRNA can be extracted, for example,from frozen or archived paraffin-embedded and fixed (e.g.formalin-fixed) tissue samples, which are routinely prepared andpreserved in everyday clinical practice.

In a specific embodiment of the microarray technique, PCR amplifiedinserts of cDNA clones are applied to a substrate in a dense array.Preferably at least 10,000 nucleotide sequences are applied to thesubstrate. The microarrayed genes, immobilized on the microchip at10,000 elements each, are suitable for hybridization under stringentconditions. Fluorescently labeled cDNA probes may be generated throughincorporation of fluorescent nucleotides by reverse transcription of RNAextracted from tissues of interest. Labeled cDNA probes applied to thechip hybridize with specificity to each spot of DNA on the array. Afterstringent washing to remove non-specifically bound probes, the chip isscanned by confocal laser microscopy or by another detection method,such as a CCD camera. Quantitation of hybridization of each arrayedelement allows for assessment of corresponding mRNA abundance. With dualcolor fluorescence, separately labeled cDNA probes generated from twosources of RNA are hybridized pairwise to the array. The relativeabundance of the transcripts from the two sources corresponding to eachspecified gene is thus determined simultaneously. The miniaturized scaleof the hybridization affords a convenient and rapid evaluation of theexpression pattern for large numbers of genes. Such methods have beenshown to have the sensitivity required to detect rare transcripts, whichare expressed at a few copies per cell, and to reproducibly detect atleast approximately two-fold differences in the expression levels(Schena et al., Proc. Natl. Acad. Sci. USA 93(2):106-149 (1996)).Microarray analysis can be performed by commercially availableequipment, following manufacturer's protocols, such as by using theAffymetrix GenChip technology, or Incyte's microarray technology.

The development of microarray methods for large-scale analysis of geneexpression makes it possible to search systematically for molecularmarkers of cancer classification and outcome prediction in a variety oftumor types.

4. Serial Analysis of Gene Expression (SAGE)

Serial analysis of gene expression (SAGE) is a method that allows thesimultaneous and quantitative analysis of a large number of genetranscripts, without the need of providing an individual hybridizationprobe for each transcript. First, a short sequence tag (about 10-14 bp)is generated that contains sufficient information to uniquely identify atranscript, provided that the tag is obtained from a unique positionwithin each transcript. Then, many transcripts are linked together toform long serial molecules, that can be sequenced, revealing theidentity of the multiple tags simultaneously. The expression pattern ofany population of transcripts can be quantitatively evaluated bydetermining the abundance of individual tags, and identifying the genecorresponding to each tag. For more details see, e.g. Velculescu et al.,Science 270:484-487 (1995); and Velculescu et al., Cell 88:243-51(1997).

5. MassARRAY Technology

The MassARRAY (Sequenom, San Diego, Calif.) technology is an automated,high-throughput method of gene expression analysis using massspectrometry (MS) for detection. According to this method, following theisolation of RNA, reverse transcription and PCR amplification, the cDNAsare subjected to primer extension. The cDNA-derived primer extensionproducts are purified, and dipensed on a chip array that is pre-loadedwith the components needed for MALTI-TOF MS sample preparation. Thevarious cDNAs present in the reaction are quantitated by analyzing thepeak areas in the mass spectrum obtained.

6. Gene Expression Analysis by Massively Parallel Signature Sequencing(MPSS

This method, described by Brenner et al. Nature Biotechnology 18:630-634(2000), is a sequencing approach that combines non-gel-based signaturesequencing with in vitro cloning of millions of templates on separate 5μm diameter microbeads. First, a microbead library of DNA templates isconstructed by in vitro cloning. This is followed by the assembly of aplanar array of the template-containing microbeads in a flow cell at ahigh density (typically greater than 3×10⁶ microbeads/cm²). The freeends of the cloned templates on each microbead are analyzedsimultaneously, using a fluorescence-based signature sequencing methodthat does not require DNA fragment separation. This method has beenshown to simultaneously and accurately provide, in a single operation,hundreds of thousands of gene signature sequences from a yeast cDNAlibrary.

7. Immunohistochemistry

Immunohistochemistry methods are also suitable for detecting theexpression levels of the prognostic markers of the present invention.Thus, antibodies or antisera, preferably polyclonal antisera, and mostpreferably monoclonal antibodies specific for each marker are used todetect expression. The antibodies can be detected by direct labeling ofthe antibodies themselves, for example, with radioactive labels,fluorescent labels, hapten labels such as, biotin, or an enzyme such ashorse radish peroxidase or alkaline phosphatase. Alternatively,unlabeled primary antibody is used in conjunction with a labeledsecondary antibody, comprising antisera, polyclonal antisera or amonoclonal antibody specific for the primary antibody.Immunohistochemistry protocols and kits are well known in the art andare commercially available.

8. Proteomics

The term “proteome” is defined as the totality of the proteins presentin a sample (e.g. tissue, organism, or cell culture) at a certain pointof time. Proteomics includes, among other things, study of the globalchanges of protein expression in a sample (also referred to as“expression proteomics”). Proteomics typically includes the followingsteps: (1) separation of individual proteins in a sample by 2-D gelelectrophoresis (2-D PAGE); (2) identification of the individualproteins recovered from the gel, e.g. my mass spectrometry or N-terminalsequencing, and (3) analysis of the data using bioinformatics.Proteomics methods are valuable supplements to other methods of geneexpression profiling, and can be used, alone or in combination withother methods, to detect the products of the prognostic markers of thepresent invention.

9. Improved Method for Isolation of Nucleic Acid from Archived TissueSpecimens

In the first step of the method of the invention, total RNA is extractedfrom the source material of interest, including fixed, paraffin-embeddedtissue specimens, and purified sufficiently to act as a substrate in anenzyme assay. While extration of total RNA can be performed by anymethod known in the art, in a particular embodiment, the inventionrelies on an improved method for the isolation of nucleic acid fromarchived, e.g. fixed, paraffin-embedded tissue specimens (FPET).

Measured levels of mRNA species are useful for defining thephysiological or pathological status of cells and tissues. RT-PCR (whichis discussed above) is one of the most sensitive, reproducible andquantitative methods for this “gene expression profiling”.Paraffin-embedded, formalin-fixed tissue is the most widely availablematerial for such studies. Several laboratories have demonstrated thatit is possible to successfully use fixed-paraffin-embedded tissue (FPET)as a source of RNA for RT-PCR (Stanta et al., Biotechniques 11:304-308(1991); Stanta et al., Methods Mol. Biol. 86:23-26 (1998); Jackson etal., Lancet 1:1391 (1989); Jackson et al., J. Clin. Pathol. 43:499-504(1999); Finke et al., Biotechniques 14:448-453 (1993); Goldsworthy etal., Mol. Carcinog. 25:86-91 (1999); Stanta and Bonin, Biotechniques24:271-276 (1998); Godfrey et al., J. Mol. Diagnostics 2:84 (2000);Specht et al. J. Mol. Med. 78:B27 (2000); Specht et al., Am. J. Pathol.158:419-429 (2001)). This allows gene expression profiling to be carriedout on the most commonly available source of human biopsy specimens, andtherefore potentially to create new valuable diagnostic and therapeuticinformation.

The most widely used protocols utilize hazardous organic solvents, suchas xylene, or octane (Finke et al., supra) to dewax the tissue in theparaffin blocks before nucleic acid (RNA and/or DNA) extraction.Obligatory organic solvent removal (e.g. with ethanol) and rehydrationsteps follow, which necessitate multiple manipulations, and addition ofsubstantial total time to the protocol, which can take up to severaldays. Commercial kits and protocols for RNA extraction from FPET[MasterPure™ Complete DNA and RNA Purification Kit (EPICENTRE®, Madison,Wis.); Paraffin Block RNA Isolation Kit (Ambion, Inc.) and RNeasy™ Minikit (Qiagen, Chatsworth, Calif.)] use xylene for deparaffinization, inprocedures which typically require multiple centrifugations and ethanolbuffer changes, and incubations following incubation with xylene.

The method that can be used in the present invention provides animproved nucleic acid extraction protocol that produces nucleic acid, inparticular RNA, sufficiently intact for gene expression measurements.The key step in this improved nucleic acid extraction protocol is theperformance of dewaxing without the use of any organic solvent, therebyeliminating the need for multiple manipulations associated with theremoval of the organic solvent, and substantially reducing the totaltime to the protocol. According to the improved method, wax, e.g.paraffin is removed from wax-embedded tissue samples by incubation at65-75° C. in a lysis buffer that solubilizes the tissue and hydrolyzesthe protein, following by cooling to solidify the wax.

FIG. 2 shows a flow chart of the improved RNA extraction protocol usedherein in comparison with a representative commercial method, usingxylene to remove wax. The times required for individual steps in theprocesses and for the overall processes are shown in the chart. Asshown, the commercial process requires approximately 50% more time thanthe improved process used in performing the methods of the invention.

The lysis buffer can be any buffer known for cell lysis. It is, however,preferred that oligo-dT-based methods of selectively purifyingpolyadenylated mRNA not be used to isolate RNA for the presentinvention, since the bulk of the mRNA molecules are expected to befragmented and therefore will not have an intact polyadenylated tail,and will not be recovered or available for subsequent analytical assays.Otherwise, any number of standard nucleic acid purification schemes canbe used. These include chaotrope and organic solvent extractions,extraction using glass beads or filters, salting out and precipitationbased methods, or any of the purification methods known in the art torecover total RNA or total nucleic acids from a biological source.

Lysis buffers are commercially available, such as, for example, fromQiagen, EpiCentre, or Ambion. A preferred group of lysis bufferstypically contains urea, and Proteinase K or other protease. ProteinaseK is very useful in the isolation of high quality, undamaged DNA or RNA,since most mammalian DNases and RNases are rapidly inactivated by thisenzyme, especially in the presence of 0.5-1% sodium dodecyl sulfate(SDS). This is particularly important in the case of RNA, which is moresusceptible to degradation than DNA. While DNases require metal ions foractivity, and can therefore be easily inactivated by chelating agents,such as EDTA, there is no similar co-factor requirement for RNases.

Cooling and resultant solidification of the wax permits easy separationof the wax from the total nucleic acid, which can be convenientlyprecipitated, e.g. by isopropanol. Further processing depends on theintended purpose. If the proposed method of RNA analysis is subject tobias by contaminating DNA in an extract, the RNA extract can be furthertreated, e.g. by DNase, post purification to specifically remove DNAwhile preserving RNA. For example, if the goal is to isolate highquality RNA for subsequent RT-PCR amplification, nucleic acidprecipitation is followed by the removal of DNA, usually by DNasetreatment. However, DNA can be removed at various stages of nucleic acidisolation, by DNase or other techniques well known in the art.

While the advantages of the improved nucleic acid extraction discussedabove are most apparent for the isolation of RNA from archived, paraffinembedded tissue samples, the wax removal step of the present invention,which does not involve the use of an organic solvent, can also beincluded in any conventional protocol for the extraction of totalnucleic acid (RNA and DNA) or DNA only.

By using heat followed by cooling to remove paraffin, the improvedprocess saves valuable processing time, and eliminates a series ofmanipulations, thereby potentially increasing the yield of nucleic acid.

10. 5′-multiplexed Gene Specific Priming of Reverse Transcription

RT-PCR requires reverse transcription of the test RNA population as afirst step. The most commonly used primer for reverse transcription isoligo-dT, which works well when RNA is intact. However, this primer willnot be effective when RNA is highly fragmented as is the case in FPEtissues.

The present invention includes the use of gene specific primers, whichare roughly 20 bases in length with a Tm optimum between about 58° C.and 60° C. These primers will also serve as the reverse primers thatdrive PCR DNA amplification.

An alternative approach is based on the use of random hexamers asprimers for cDNA synthesis. However, we have experimentally demonstratedthat the method of using a multiplicity of gene-specific primers issuperior over the known approach using random hexamers.

11. Normalization Strategy

An important aspect of the present invention is to use the measuredexpression of certain genes by EGFR-expressing cancer tissue to provideinformation about the patient's likely response to treatment with anEGFR-inhibitor. For this purpose it is necessary to correct for(normalize away) both differences in the amount of RNA assayed andvariability in the quality of the RNA used. Therefore, the assaytypically measures and incorporates the expression of certainnormalizing genes, including well known housekeeping genes, such asGAPDH and Cyp1. Alternatively or in addition, normalization can be basedon the mean or median signal (Ct in the case of RT-PCR) of all of theassayed genes or a large subset thereof (global normalization approach).On a gene-by-gene basis, measured normalized amount of a patient tumormRNA is compared to the amount found in a reference set of cancer tissueof the same type (e.g. head and neck cancer, colon cancer, etc.). Thenumber (N) of cancer tissues in this reference set should besufficiently high to ensure that different reference sets (as a whole)behave essentially the same way. If this condition is met, the identityof the individual cancer tissues present in a particular set will haveno significant impact on the relative amounts of the genes assayed.Usually, the cancer tissue reference set consists of at least about 30,preferably at least about 40 different FPE cancer tissue specimens.Unless noted otherwise, normalized expression levels for eachmRNA/tested tumor/patient will be expressed as a percentage of theexpression level measured in the reference set. More specifically, thereference set of a sufficiently high number (e.g. 40) of tumors yields adistribution of normalized levels of each mRNA species. The levelmeasured in a particular tumor sample to be analyzed falls at somepercentile within this range, which can be determined by methods wellknown in the art. Below, unless noted otherwise, reference to expressionlevels of a gene assume normalized expression relative to the referenceset although this is not always explicitly stated.

12. EGFR Inhibitors

The epidermal growth factor receptor (EGFR) family (which includes EGFR,erb-B2, erb-B3, and erb-B4) is a family of growth factor receptors thatare frequently activated in epithelial malignancies. Thus, the epidermalgrowth factor receptor (EGFR) is known to be active in several tumortypes, including, for example, ovarian cancer, pancreatic cancer,non-small cell lung cancer, breast cancer, colon cancer and head andneck cancer. Several EGFR inhibitors, such as ZD1839 (also known asgefitinib or Iressa); and OSI774 (Erlotinib, Tarceva™), are promisingdrug candidates for the treatment of EGFR-expressing cancer.

Iressa, a small synthetic quinazoline, competitively inhibits the ATPbinding site of EGFR, a growth-promoting receptor tyrosine kinase, andhas been in Phase III clinical trials for the treatment ofnon-small-cell lung carcinoma. Another EGFR inhibitor,[agr]cyano-[bgr]methyl-N-[(trifluoromethoxy)phenyl]-propenamide(LFM-A12), has been shown to inhibit the proliferation and invasivenessof EGFR positive human breast cancer cells.

Cetuximab is a monoclonal antibody that blocks the EGFR andEGFR-dependent cell growth. It is currently being tested in phase IIIclinical trials.

Tarceva™ has shown promising indications of anti-cancer activity inpatients with advanced ovarian cancer, and non-small cell lung and headand neck carcinomas.

The present invention provides valuable tools to predict whether anEGFR-positive tumor is likely to respond to treatment with anEGFR-inhibitor.

Recent publications further confirm the involvement of EGFR ingastrointestinal (e.g. colon) cancer, and associate its expression withpoor survival. See, e.g. Khorana et al., Proc. Am. Soc. Clin. Oncol22:317 (2003).

While the listed examples of EGFR inhibitors a small organic molecules,the findings of the present invention are equally applicable to otherEGFR inhibitors, including, without limitation, anti-EGFR antibodies,antisense molecules, small peptides, etc.

Further details of the invention will be apparent from the followingnon-limiting Examples.

Example 1 A Phase II Study of Gene Expression in Head and Neck Tumors

A gene expression study was designed and conducted with the primary goalto molecularly characterize gene expression in paraffin-embedded, fixedtissue samples of head and neck cancer patients who responded or did notrespond to treatment with an EGFR inhibitor. The results are based onthe use of five different EGFR inhibitor drugs.

Study Design

Molecular assays were performed on paraffin-embedded, formalin-fixedhead and neck tumor tissues obtained from 14 individual patientsdiagnosed with head and neck cancer. Patients were included in the studyonly if histopathologic assessment, performed as described in theMaterials and Methods section, indicated adequate amounts of tumortissue.

Materials and Methods

Each representative tumor block was characterized by standardhistopathology for diagnosis, semi-quantitative assessment of amount oftumor, and tumor grade. A total of 6 sections (10 microns in thicknesseach) were prepared and placed in two Costar Brand Microcentrifuge Tubes(Polypropylene, 1.7 mL tubes, clear; 3 sections in each tube). If thetumor constituted less than 30% of the total specimen area, the samplemay have been crudely dissected by the pathologist, using grossmicrodissection, putting the tumor tissue directly into the Costar tube.

If more than one tumor block was obtained as part of the surgicalprocedure, all tumor blocks were subjected to the same characterization,as described above, and the block most representative of the pathologywas used for analysis.

Gene Expression Analysis

mRNA was extracted and purified from fixed, paraffin-embedded tissuesamples, and prepared for gene expression analysis as described above.

Molecular assays of quantitative gene expression were performed byRT-PCR, using the ABI PRISM 7900™ Sequence Detection System™(Perkin-Elmer-Applied Biosystems, Foster City, Calif., USA). ABI PRISM7900™ consists of a thermocycler, laser, charge-coupled device (CCD),camera and computer. The system amplifies samples in a 384-well formaton a thermocycler. During amplification, laser-induced fluorescentsignal is collected in real-time through fiber optics cables for all 384wells, and detected at the CCD. The system includes software for runningthe instrument and for analyzing the data.

Analysis and Results

Tumor tissue was analyzed for 185 cancer-related genes and 7 referencegenes. The threshold cycle (CT) values for each patient were normalizedbased on the mean of all genes for that particular patient. Clinicaloutcome data were available for all patients.

Outcomes were classified as either response or no response. The resultswere analyzed in two different ways using two different criteria forresponse: partial response, or clinical benefit. The latter criterioncombines partial or complete response with stable disease (minimum 3months). In this study, there were no complete responses, four cases ofpartial response and two cases of disease stabilization.

We evaluated the relationship between gene expression and partialresponse by logistic regression and have identified the following genesas significant (p<0.15), as indicated in the attached Table 1. Thelogistic model provides a means of predicting the probability (Pr) of asubject as being either a partial responder or not. The followingequation defined the expression threshold for response.

${\Pr ({Response})} = \frac{1}{1 + ^{{Intercept} + {SlopexReferenceNormalizedCT}}}$and Pr (No  Response) = 1 − Pr (Response)

In Table 1, the term “negative” indicates that greater expression of thegene decreased likelihood of response to treatment with EGFR inhibitor,and “positive” indicates that increased expression of the gene increasedlikelihood of response to EGFR inhibitor. Results from analysis of headand neck cancer patient data using clinical benefit criteria are shownin Table 2.

Overall increased expression of the following genes correlated withresistance of head and neck cancer to EGFR inhibitor treatment:A-Catenin; AKT1; AKT2; APC; Bax; B-Catenin; BTC; CCNA2; CCNE1; CCNE2;CD105; CD44v3; CD44v6; CD68; CEACAM6; Chk2; cMet; COX2; cripto; DCR3;DIABLO; DPYD; DR5; EDN1 endothelin; EGFR; ELF4E; ERBB4; ERK1; fas; FRP1;GRO1; HB-EGF; HER2; IGF1R; IRS1; ITGA3; KRT17; LAMC2; MTA1; NMYC; PAI1;PDGFA; PGK1; PTPD1; RANBP2; SPRY2; TP53BP1; and VEGFC; and increasedexpression of the following genes correlated with response of head andneck cancer to EGFR inhibitor treatment: CD44s; CD82; CGA; CTSL;EGFRd27; IGFBP3; p27; P53; RB1; TIMP2; and YB-1.

Example 2 A Phase II Study of Gene Expression in Colon Cancer

In a study analogous to the study of head and neck cancer patientsdescribed in Example 1, gene expression markers were sought thatcorrelate with increased or decreased likelihood of colon cancerresponse to EGFR inhibitors. Sample preparation and handling and geneexpression and data analysis were performed as in Example 1.

Twenty-three colon adenocarcinoma patients in all were studied, using a192 gene assay. 188 of the 192 genes were expressed above the limit ofdetection. Both pathological and clinical responses were evaluated.Following treatment with EGFR inhibitor, three patients were determinedto have had a partial response, five to have stable disease and fifteento have progressive disease.

Table 3 shows the results obtained using the partial response criterion.

Results from analysis of colon cancer patient data using clinicalbenefit criteria are shown in Table 4.

Overall, increased expression of the following genes correlated withresistance of colon cancer to EGFR inhibitor treatment: CA9; CD134;CD44E; CD44v3; CD44v6; CDC25B; CGA; DR5; GRO1; KRT17; LAMC2; P14ARF;PDGFB; PLAUR; PPARG; RASSF1; RIZ1; Src; TFRC; and UPA, and increasedexpression of the following genes correlated with sensitivity of coloncancer to EGFR inhibitor treatment: CD44s; CD82; CGA; CTSL; EGFRd27;IGFBP3; p27; P53; RB1; TIMP2; and YB-1.

Finally, it is noteworthy that increased expression of the followinggenes correlated with resistance to EGFR inhibitor treatment in bothhead and neck and colon cancer: CD44v3; CD44v6; DR5; GRO1; KRT17; LAMC2.

In similar experiments, the elevated expression of LAMC2, B-Catenin,Bax, GRO1, Fas, or ITGA3 in EGFR-positive head and neck cancer wasdetermined to be an indication that the patient is not likely to respondwell to treatment with an EGFR inhibitor. On the other hand, elevatedexpression of YB-1, PTEN, CTSL, P53, STAT3, ITGB3, IGFBP3, RPLPO or p27in EGFR-positive head and neck cancer was found to be an indication thatthe patient is likely to respond to EGFR inhibitor treatment.

In another set of similar experiments, elevated expression of thefollowing genes in EGFR-expressing colon cancer correlated with positiveresponse to treatment: BAK; BCL2; BRAF; BRK; CCND3; CD9; ER2; ERBB4;EREG; ERK1; FRP1. Elevated expression of the following genes inEGFR-expressing colon cancer correlated with resistance to treatment:APN; CA9; CCND1; CDC25B; CD134; LAMC2; PDGFB; CD44v6; CYP1; DR5; GAPDH;IGFBP2; PLAUR; RASSF1; UPA.

All references cited throughout the specification are hereby expresslyincorporated by reference.

Although the present invention is illustrated with reference to certainembodiments, it is not so limited. Modifications and variations arepossible without diverting from the spirit of the invention. All suchmodifications and variations, which will be apparent to those skilled inthe art, are specifically within the scope of the present invention.While the specific examples disclosed herein concern head and neckcancer and colon cancer, the methods of the present invention aregenerally applicable and can be extended to all EGFR-expressing cancers,and such general methods are specifically intended to be within thescope herein.

TABLE 1 Partial Response Genes for Head and Neck Study LogisticDiscriminat Likelihood Gene Function Ratio Test Name Response InterceptSlope R2 P Value cMet Negative 26.5168713 4.57143179 0.6662 0.0011 LAMC2Negative 5.29706425 1.28137295 0.6155 0.0017 ITGA3 Negative 22.60085443.17707499 0.5063 0.0044 CD44v6 Negative 6.92255059 4.3069909 0.4920.005 B-Catenin Negative 7.85913706 2.52965454 0.4805 0.0055 PDGFANegative 6.0016358 1.10386463 0.4318 0.0085 GRO1 Negative 8.376466351.74815793 0.4146 0.0099 ERK1 Negative 6.14712633 1.64819007 0.40240.0111 CD44v3 Negative 5.95094528 3.36594473 0.3451 0.0186 Bax Negative5.34006632 1.19383253 0.3361 0.0202 CGA Positive −78.121148 −10.5037570.3266 0.0221 fas Negative 7.27491015 1.38464586 0.3251 0.0224 IGFBP3Positive −2.1529531 −2.7937517 0.3097 0.0258 MTA1 Negative 6.071672771.23786874 0.3072 0.0264 YB-1 Positive 1.73598983 −4.0859174 0.28140.0336 DR5 Negative 9.0550349 1.46349944 0.2703 0.0373 APC Negative5.775003 1.88324269 0.2512 0.0447 ERBB4 Negative 11.9466285 1.586066970.2357 0.0518 CD68 Negative 3.60605487 1.0645631 0.2319 0.0537 criptoNegative 19.5004373 2.64909385 0.2251 0.0574 P53 Positive −4.1976158−1.5541169 0.2208 0.0598 VEGFC Negative 6.33634489 0.90613473 0.22080.0598 A-Catenin Negative 4.41215235 1.7591194 0.2199 0.0603 COX2Negative 8.00968996 1.27597736 0.202 0.0718 CD82 Positive −1.8999985−1.171157 0.1946 0.0772 PAI1 Negative 2.94777884 0.97480364 0.19440.0774 AKT2 Negative 2.45598587 1.64608189 0.1889 0.0817 HER2 Negative4.25059223 0.97748483 0.1845 6.0853 DIABLO Negative 17.035069 2.939397410.1809 0.0884 p27 Positive −1.9798519 −1.9041142 0.1792 0.09 RANBP2Negative 2.85994976 0.41878666 0.1757 0.0931 EIF4E Negative 2.912027680.56099402 0.1722 0.0965 EDN1 endothelin Negative 6.06858911 0.871855530.1688 0.0998 IGF1R Negative 6.14387144 1.68865744 0.1674 0.1012 AKT1Negative 5.02676228 1.50585593 0.1659 0.1028 CCNA2 Negative 3.956845590.63089954 0.184 0.1033 HB-EGF Negative 5.1019713 0.70368632 0.16270.1061 TIMP2 Positive 2.58975885 −1.0832648 0.1625 0.1064 EGFRd27Positive −38.789016 −5.2513587 0.1607 0.1083 Chk2 Negative 6.87971751.21671205 0.1581 0.1112 IRS1 Negative 12.0545078 1.59632708 0.15780.1115 FRP1 Negative 3.38233862 0.49053452 0.1569 0.1126 CCNE2 Negative5.78828731 1.11609099 0.1566 0.1129 SPRY2 Negative 4.68447069 0.867478030.1552 0.1145 KRT17 Negative 0.34280253 0.412313 0.151 0.1195 DPYDNegative 2.78071456 0.78918833 0.1504 0.1202 CD105 Negative 3.136137330.51406689 0.1391 0.1351 TP53BP1 Negative 3.18676588 0.58622276 0.13610.1395 PTPD1 Negative 5.85217342 1.08545385 0.1357 0.1401 CTSL Positive−2.2283797 −1.4833372 0.1354 0.1405

TABLE 2 Clinical Benefit Genes for Head and Neck Study LogisticDiscriminat Likelihood Gene Function Ratio Test Name Response InterceptSlope R² P Value cMet.2 Negative 23.583252 4.4082875 0.6444 0.0007GRO1.2 Negative 10.10717 2.46904056 0.5388 0.0019 A-Catenin.2 Negative5.13298651 2.60834812 0.3628 0.0107 AKT1.3 Negative 7.7652606 2.830680920.3044 0.0194 DCR3.3 Negative 10.2957141 1.85012996 0.293 0.0219B-Catenin.3 Negative 4.21267279 1.5417788 0.2791 0.0252 EDN1endothelin.1 Negative 6.83022814 1.14550062 0.2758 0.0261 CCNE1.1Negative 7.43731399 1.21270723 0.2661 0.0289 LAMC2.2 Negative 1.796598620.56623898 0.2498 0.0342 CD44v6.1 Negative 2.55050577 1.87838162 0.20710.0539 DIABLO.1 Negative 16.5051841 2.99910512 0.2066 0.0542 CD44v3.2Negative 3.02492619 2.05469571 0.2002 0.058 NMYC.2 Negative 23.20103273.20767305 0.1955 0.061 CD82.3 Positive −2.7521937 −1.1692268 0.1880.0662 RANBP2.3 Negative 2.02076788 0.42173233 0.1807 0.0718 RB1.1Positive −5.7352964 −1.7540651 0.1761 0.0754 HER2.3 Negative 3.875641581.11486016 0.1732 0.0779 MTA1.1 Negative 3.9020256 0.92255645 0.16280.0874 CGA.3 Positive −41.909839 −5.5686182 0.1619 0.0883 CEACAM6.1Negative 1.66596967 0.59307792 0.1602 0.0899 PTPD1.2 Negative 5.512427631.18616068 0.1601 0.0901 ERK1.3 Negative 2.4144706 0.72072834 0.1540.0964 Bax.1 Negative 2.91338256 0.76334619 0.152 0.0987 STMY3.3Positive −0.9946728 −0.6053981 0.1483 0.1028 COX2.1 Negative 5.792796161.0312018 0.1478 0.1034 EIF4E.1 Negative 2.08005397 0.55985052 0.14680.1045 YB-1.2 Positive 0.45158771 −2.2935538 0.1426 0.1096 fas.1Negative 4.05538424 0.8686042 0.1397 0.1134 PDGFA.3 Negative 2.433882750.53168307 0.1371 0.1168 FRP1.3 Negative 2.17320245 0.41529609 0.1370.1169 PGK1.1 Negative 1.86416703 1.92395917 0.1338 0.1212 AKT2.3Negative 1.45131206 1.43341036 0.1281 0.1294 BTC.3 Negative 12.11537341.67411928 0.1281 0.1294 APC.4 Negative 2.50791938 0.92506412 0.1280.1296 CCNE2.2 Negative 3.98727145 0.89372321 0.1267 0.1315 OPN,osteopontin.3 Positive −0.522697 −0.5069258 0.1225 0.1382 ITGA3.2Negative 2.23381763 0.3800099 0.1203 0.1417 KRT17.2 Negative −0.48611690.43917211 0.1184 0.1449 CD44s.1 Positive −0.9768133 −0.8896223 0.1180.1456 EGFR.2 Negative 0.43258354 0.46719029 0.1162 0.1487

TABLE 3 Partial Response Genes for Colon Study Logistic DiscriminatLikelihood Gene Function Ratio Test Name Response Intercept Slope R² PValue Bclx_2 Positive 2.04896151 −2.1025144 0.172 0.0801 BRAF_2 Positive−2.5305788 −3.0987684 0.2532 0.0337 BRK_2 Positive −2.6096501 −1.5773880.2998 0.0209 CA9_3 Negative 2.65287578 0.83720397 0.2758 0.0267 Cad17_1Positive −0.0419396 −1.8773242 0.2096 0.0533 CCND3_1 Positive −1.014844−5.1111617 0.348 0.0128 CCNE1_1 Positive −6.5821701 −0.8939912 0.19140.0648 CCNE2_2 Positive 26.1675642 −1.0709109 0.1707 0.0812 CD105_1Positive 5.85359096 −1.2349006 0.1302 0.1278 CD134_2 Negative −5.92865761.51119518 0.1212 0.1418 CD44v3_2 Negative −1.8184898 1.12771829 0.20640.0552 CDC25B_1 Negative 10.4351019 1.59196005 0.2455 0.0365 DR5_2Negative −1.7399226 1.60177588 0.1759 0.0767 ErbB3_1 Positive 3.65681435−0.760436 0.1222 0.1401 EREG_1 Positive −2.3409861 −1.1217612 0.25420.0333 GPC3_1 Positive 4.03889935 −1.9097648 0.3752 0.0097 GRO1.2Negative 2.77545378 0.74734483 0.124 0.1359 GUS_1 Positive 8.29578416−1.9015759 0.2105 0.0529 HGF_4 Positive 5.10609383 −1.1947949 0.23610.0403 ID1_1 Positive 10.6703203 −1.654146 0.216 0.0498 ITGB3_1 Positive0.79232612 −0.827508 0.3321 0.015 KRT17_2 Negative 5.93738146 0.935146330.2133 0.0513 LAMC2_2 Negative −0.3325052 1.41542034 0.2475 0.0357P14ARF_1 Negative 4.36456658 4.10859002 0.2946 0.022 PDGFB_3 Negative−4.7055966 1.96517114 0.3299 0.0154 PLAUR_3 Negative 7.518176460.6862142 0.1534 0.0983 PTPD1_2 Positive −11.659761 −1.2559081 0.12470.1362 RASSF1_3 Negative 6.60631474 0.9862129 0.1708 0.0811 RIZ1_2Negative 2.83817546 0.86281199 0.1255 0.1349 Src_2 Negative 4.913641451.96089745 0.1324 0.1247 TFRC_3 Negative −4.0754666 3.03617052 0.190.0658 TITF1_1 Positive −1.8849815 −2.1890987 0.1349 0.1211 upa_3Negative 4.1059421 1.14053848 0.1491 0.1032 XIAP_1 Positive −16.296951−2.9502191 0.2661 0.0295

TABLE 4 Clinical Benefit Genes for Colon Study Logistic DiscriminatLikelihood Gene Function Ratio Test Name Response Intercept Slope R² PValue Bak Positive −1.347937 −0.993212 0.1189 0.0602 BRK Positive−3.237705 −1.1479379 0.2567 0.0057 CD134 Negative 9.9358537 1.684401490.1927 0.0167 CD44E Negative 3.188991 0.59091622 0.0958 0.0916 CD44v6Negative 5.7352464 1.77571293 0.2685 0.0047 CDC25B Negative 2.06642090.67140598 0.0783 0.1272 CGA Negative 2.7903424 0.43834476 0.1035 0.0794COX2 Positive −1.262804 −0.4741852 0.0733 0.1398 DIABLO Positive−2.514199 −1.0753148 0.1028 0.0805 FRP1 Positive −0.401936 −0.35558990.0937 0.0952 GPC3 Positive −7.875276 −1.7437079 0.3085 0.0025 HER2Positive 0.1228609 −0.5549133 0.073 0.1408 ITGB3 Positive −1.593092−0.5249778 0.1352 0.045 PPARG Negative 8.6479233 1.36115361 0.10490.0774 PTPD1 Positive −3.203607 −1.2049773 0.1356 0.0447 RPLPO Positive3.5110353 −1.030518 0.0752 0.135 STK15 Positive −0.664989 −0.59364750.0873 0.1072 SURV Positive −1.409619 −0.6214924 0.074 0.1381 TERCPositive 1.7755749 −0.5180083 0.1073 0.0742 TGFBR2 Positive 1.5172396−0.9288498 0.0934 0.0957

TABLES 5A-5B Seq.  Gene Accessin Sequence ID A-Catenin NM_00190CGTTCCGATCCTCTATACTGCATCCCAGGCATGCCTACAGCACCCTGATGTCGCAGCCTATAAGGCCAACA1 GGGACCT AKT1 NM_00516CGCTTCTATGGCGCTGAGATTGTGTCAGCCCTGGACTACCTGCACTCGGAGAAGAACGTGGTGTACCGGGA2 AKT2 NM_00162TCCTGCCACCCTTCAAACCTCAGGTCACGTCCGAGGTCGACACAAGGTACTTCGATGATGAATTTACCGCC3 APC NM_00003GGACAGCAGGAATGTGTTTCTCCATACAGGTCACGGGGAGCCAATGGTTCAGAAACAAATCGAGTGGGT 4B-Catenin NM_00190GGCTCTTGTGCGTACTGTCCTTCGGGCTGGTGACAGGGAAGACATCACTGAGCCTGCCATCTGTGCTCTTC5 GTCATCTGA Bak NM_00118CCATTCCCACCATTCTACCTGAGGCCAGGACGTCTGGGGTGTGGGGATTGGTGGGTCTATGTTCCC 6 BaxNM_0432CCGCCGTGGACACAGACTCCCCCCGAGAGGTCTTTTTCCGAGTGGCAGCTGACATGTTTTCTGACGGCAA 7Bclx NM_00119CTTTTGTGGAACTCTATGGGAACAATGCAGCAGCCGAGAGCCGAAAGGGCCAGGAACGCTTCAACCGCTG 8BRAF NM_00433CCTTCCGACCAGCAGATGAAGATCATCGAAATCAATTTGGGCAACGAGACCGATCCTCATCAGCTCCCAAT9 GTGCATATAAA BRK NM_00597GTGCAGGAAAGGTTCACAAATGTGGAGTGTCTGCGTCCAATACACGCGTGTGCTCCTCTCCTTACTCCATG10 GTGTGTGC BTC NM_00172AGGGAGATGCCGCTTCGTGGTGGCCGAGCAGACGCCCTCCTGTGTCTGTGATGAAGGCTACATTGGAGCAA11 GGTGTGAGAG CA9 NM_00121ATCCTAGCCCTGGTTTTTGGCCTCCTTTTTGCTGTCACCAGCGTCGCGTTCCTTGTGCAGATGAGAAGGCA12 G Cad17 NM_00406GAAGGCCAAGAACCGAGTCAAATTATATTCCAGTTTAAGGCCAATCCTCCTGCTGTGACTTTTGAACTAAC13 TGGGGA CCNA2 NM_00123CCATACCTCAAGTATTTGCCATCAGTTATTGCTGGAGCTGCCTTTCATTTAGCACTCTACACAGTCACGGG14 ACAAAGCT CCND3 NM_00176CCTCTGTGCTACAGATTATACCTTTGCCATGTACCCGCCATCCATGATCGCCACGGGCAGCATTGGGGCTG15 CAGTG CCNE1 NM_00123AAAGAAGATGATGACCGGGTTTACCCAAACTCAACGTGCAAGCCTCGGATTATTGCACCATCCAGAGGCTC16 CCNE2 NM_05774ATGCTGTGGCTCCTTCCTAACTGGGGCTTTCTTGACATGTAGGTTGCTTGGTAATAACCTTTTTGTATATC17 ACAATTTGGGT CD105 NM_00011GCAGGTGTCAGCAAGTATGATCAGCAATGAGGCGGTGGTCAATATCCTGTCGAGCTCATCACCACAGCGGA18 AAAA CD134 NM_00332GCCCAGTGCGGAGAACAGGTCCAGCTTGATTCTCGTCTCTGCACTTAAGCTGTTCTCCAGGTGCGTGTGAT19 T CD44E X55150ATCACCGACAGCACAGACAGAATCCCTGCTACCAATATGGACTCCAGTCATAGTACAACGCTTCAGCCTAC20 TGCAAATCCAAACACAGGT CD44s M59040GACGAAGACAGTCCCTGGATCACCGACAGCACAGACAGAATCCCTGCTACCAGAGACCAAGACACATTCCA21 CCCCAGT CD44v3 AJ251595CACACAAAACAGAACCAGGACTGGACCCAGTGGAACCCAAGCCATTCAAATCCGGAAGTGCTACTTCAG 22CD44v6 AJ251595CTCATACCAGCCATCCAATGCAAGGAAGGACAACACCAAGCCCAGAGGACAGTTCCTGGACTGATTTCTTC23 AACCCAA CD68 NM_00125TGGTTCCCAGCCCTGTGTCCACCTCCAAGCCCAGATTCAGATTCGAGTCATGTACACAACCCAGGGTGGAG24 GAG CD82 NM_00223GTGCAGGCTCAGGTGAAGTGCTGCGGCTGGGTCAGCTTCTACAACTGGACAGACAACGCTGAGCTCATGAA25 TCGCCCTGAGGTC CD9 NM_00176GGGCGTGGAACAGTTTATCTCAGACATCTGaCCCAAGAAGGACGTACTCGAAACCTTCACCGTG 26CDC25B NM_02187AAACGAGCAGTTTGCCATCAGACGCTTCCAGTCTATGCCGGTGAGGCTGCTGGGCCACAGCCCCGTGCTTC27 GGAACATCACCAAC CEACAM6 NM_00248CACAGCCTCACTTCTAACCTTCTGGAACCCACCCACCACTGCCAAGCTCACTATTGAATCCACGCCATTCA28 A CGA NM_00127CTGAAGGAGCTCCAAGACCTCGCTCTCCAAGGCGCCAAGGAGAGGGCACATCAGCAGAAGAAACACAGCGG29 TTTTG Chk2 NM_00719ATGTGGAACCCCCACCTACTTGGCGCCTGAAGTTCTTGTTTCTGTTGGGACTGCTGGGTATAACCGTGCTG30 TGGACTG cMet NM_00024GACATTTCCAGTCCTGCAGTCAATGCCTCTCTGCCCCACCCTTTGTTCAGTOTGGCTGGTGCCACGACAAA31 TGTGTGCGATCGGAG COX2 NM_00096TCTGCAGAGTTGGAAGCACTCTATGGTGACATCGATGCTGTGGAGCTGTATCCTGCCCTTCTGGTAGAAAA32 GCCTCGGC cripto  NM_00321GGGTCTGTGCCCCATGACACCTGGCTGCCCAAGAAGTGTTCCCTGTGTAAATGCTGGCACGGTCA 33CTSL NM_00191GGGAGGCTTATCTCACTGAGTGAGCAGAATCTGGTAGACTGCTCTGGGCCTCAAGGCAATGAAGGCTGCAA34 TGG DCR3 NM_01643GACCAAGGTCCTGGAATGTCTGCAGCAGAAGGTGAATGGCATCCTGGAGAGCCCTACGGGTACAGGGAAGA35 C DIABLO NM_01988CACAATGGCGGCTCTGAAGAGTTGGCTGTCGCGCAGCGTAACTTCATTCTTCAGGTACAGACAGTGTTTGT36 GT DPYD NM 00011AGGACGCAAGGAGGGTTTGTCACTGGCAGACTCGAGACTGTAGGCACTGCCATGGCCCCTGTGCTCAGTAA37 GGACTCGGCGGACATC DR5 NM_00384CTCTGAGACAGTGCTTCGATGACTTTGCAGACTTGGTGCCCTTTGACTCCTGGGAGCCGCTCATGAGGAAG38 TTGGGCCTCATGG EDN1 end NM_00195TGCCACCTGGACATCATTTGGGTCAACACTCCCGAGCACGTTGTTCCGTATGGACTTGGAAGCCCTAGGTC39 CA EGFR NM_00522TGTCGATGGACTTCCAGAACCACCTGGGCAGCTGCCAAAAGTGTGATCCAAGCTGTCCCAAT 40EGFRd27 EGFRd27GAGTCGGGCTCTGGAGGAAAAGAAAGGTAATTATGTGGTGACAGATCACGGCTCGTGCGTCCGAGCCTGTG41 G EIF4E NM_00196GATCTAAGATGGCGACTGTCGAACCGGAAACCACCCCTACTCCTAATCCCCCGACTACAGAAGAGGAGAAA42 ACGGAATCTAA ErbB3 NM_00198CGGTTATGTCATGCCAGATACACACCTCAAAGGTACTCCCTCCTCCCGGGAAGGCACCCTTTCTTCAGTGG43 GTCTCAGTTC ERBB4 NM_00523TGGCTCTTAATCAGTTTCGTTACCTGCCTCTGGAGAATTTACGCATTATTCGTGGGACAAAACTTTATGAG44 GATCGATATGCCTTG EREG NM_00143ATAACAAAGTGTAGCTCTGACATGAATGGCTATTGTTTGCATGGACAGTGCATCTATCTGGTGGACATGAG45 TCAAAACTACTGCAGGTGTG ERK1 Z11-696ACGGATCACAGTGGAGGAAGCGCTGGCTCACCCCTACCTGGAGCAGTACTATGACCCGACGGATGAG 46fas NM_00004GGATTGCTCAACAACCATGCTGGGCATCTGGACCCTCCTACCTCTGGTTCTTACGTCTGTTGCTAGATTAT47 CGTCCAAAAGTGTTAATGCC FRP1 NM_00301TTGGTACCTGTGGGTTAGCATCAAGTTCTCCCCAGGGTAGAATTCAATCAGAGCTCCAGTTTGCATTTGGA48 TGTG GPC3 NM00448TGATGCGCCTGGAAACAGTCAGCAGGCAACTCCGAAGGACAACGAGATAAGCACCTTTCACAACCTCG 49GRO1 NM_0151CGAAAAGATGCTGAACAGTGACAAATCCAACTGACCAGAAGGGAGGAGGAAGCTCACTGGTGGCTGTTCCT50 GA GUS NM_00018CCCACTCAGTAGCCAAGTCACAATGTTTGGAAAACAGCCCGTTTACTTGAGCAAGACTGATACCACCTGCG51 TG HB-EGF NM_00194GACTCCTTCGTCCCCAGTTGCCGTCTAGGATTGGGCCTCCCATAATTGCTTTGCCAAAATACCAGAGCCTT52 CAAGTGCCA HER2 NM_00444CGGTGTGAGAAGTGCAGCAAGCCCTGTGCCCGAGTGTGCTATGGTCTGGGCATGGAGCACTTGCGAGAGG53 HGF M29-145CCGAAATCCAGATGATGATGCTCATGGACCCTGGTGCTACACGGGAAATCCACTCATTCCTTGGG 54 ID1NM_00216AGAACCGCAAGGTGAGCAAGGTGGAGATTCTCCAGCACGTCATCGACTACATCAGGGACCTTCAGTTGGA55 IGF1R NM_00087GCATGGTAGCCGAAGATTTCACAGTCAAAATCGGAGATTTTGGTATGACGCGAGATATCTATGAGACAGAC56 TATTACCGGAAA IGFBP3 NM_0059ACGCACCGGGTGTCTGATCCCAAGTTCCACCCCCTCCATTCAAAGATAATCATCATCAAGAAAGGGCA 57IRS1 NM_00554CCACAGCTCACCTTCTGTCAGGTGTCCATCCCAGCTCCAGCCAGCTCCCAGAGAGGAAGAGACTGGCACTG58 AGG ITGA3 NM_00220CCATGATCCTCACTCTGCTGGTGGACTATACACTCCAGACCTCGCTTAGCATGGTAAATCACCGGCTACAA59 AGCTTC ITGB3 NM_00021ACCGGGAGCCCTACATGACCGAAAATACCTGCAACCGTTACTGCCGTGACGAGATTGAGTCAGTGAAAGAG60 CTTAAGG KRT17 NM_60042CGAGGATTGGTTCTTCAGCAAGACAGAGGAACTGAACCGCGAGGTGGCCACCAACAGTGAGCTGGTGCAGA61 GT LAMC2 NM_00556ACTCAAGCGGAAATTGAAGCAGATAGGTCTTATCAGCACAGTCTCCGCCTCCTGGATTCAGTGTCTCGGCT62 TCAGGGAGT MTA1 NM_00468CCGCCCTGACCTGAAGAGAAACGCGCTCCTTGGCGGACACTGGGGGAGGAGAGGAAGAAGCGCGGCTAACT63 TATTCC NMYC NM_00537TGAGCGTCGCAGAAACCACAACATCCTGGAGCGCCAGCGCCGCAACGACCTTCGoTCCAGCTTTCTCACGC64 TCAGGGA p14ARF NM_00007GCGGAAGGTCCCTCAGACATCCCCGATTGAAAGAACCAGAGAGGCTCTGAGAAAOCTCGGGAAACTTAGA65 p27 NM_00406CGGTGGACCACGAAGAGTTAACCCGGGACTTGGAGAAGCACTGCAGAGACATGGAAGAGGCGAGCC 66P53 NM_00054CTTTGAACCCTTGCTTGCAATAGGTGTGCGTCAGAAGCACCCAGGACTTCCATTTGCTTTGTCCCGGG 67PAI1 NM_00060CCGCAACGTGGTTTTCTCACCCTATGGGGTGGCCTCGGTGTTGGCCATGCTCCAGCTGACAACAGGAGGAG68 AAACCCAGCA PDGFA NM_00260TTGTTGGTGTGCCCTGGTGCCGTGGTGGCGGTCACTCCCTCTGCTGCCAGTGTTTGGACAGAACCCA 69PDGFB NM_00260ACTGAAGGAGACCCTTGGAGCCTAGGGGCATCGGCAGGAGAGTGTGTGGGCAGGGTTATTTA 70 PGK1NM_00029AGAGCCAGTTGCTGTAGAACTCAAATCTCTGCTGGGCAAGGATGTTCTGTTCTTGAAGGACTGTGTAGGCC71 CAG PLAUR NM_00265CCCATGGATGCTCCTCTGAAGAGACTTTCCTCATTGACTGCCGAGGCCCCATGAATCAATGTCTGGTAGCC72 ACCGG PPARG NM_00503TGACTTTATGGAGCCCAAGTTTGAGTTTGCTGTGAAGTTCAATGCACTGGAATTAGATGACAGCGACTTGG73 C PTPD1 NM_0703CGCTTGCCTAACTCATACTTTCCCGTTGACACTTGATCCACGCAGCGTGGCACTGGGACGTAAGTGGCGCA74 GTCTGAATGG RANBP2 NM_00626TCCTTCAGCTTTCACACTGGGCTCAGAAATGAAGTTGCATGACTCTTCTGGAAGTCAGGTGGGAACAGGAT75 TT RASSF1 NM_00718AGTGGGAGACACCTGACCTTTCTCAAGCTGAGATTGAGCAGAAGATCAAGGAGTACAATGCCCAGATCA 76RB1 NM_00032CGAAGCCCTTACAAGTTTCCTAGTTCACCCTTACGGATTCCTGGAGGGAACATCTATATTTCACCCCTGAA77 GAGTCC RIZ1 NM_01223CCAGACGAGCGATTAGAAGCGGCAGCTTGTGAGGTGAATGATTTGGGGGAAGAGGAGGAGGAGGAAGAGGA78 GGA RPLPO NM_00100CCATTCTATCATCAACGGGTACAAACGAGTCCTGGCCTTGTCTGTGGAGACGGATTACACCTTCCCACTTG79 CTGA SPRY2 NM_00584TGTGGCAAGTGCAAATGTAAGGAGTGCACCTACCCAAGGCCTCTGCCATCAGACTGGATCTGCGAC 80Src NM_00438CCTGAACATGAAGGAGCTGAAGCTGCTGCAGACCATCGGGAAGGGGGAGTTCGGAGACGTGATG 81STK15 NM_00360CATCTTCCAGGAGGACCACTCTCTGTGGCACCCTGGACTACCTGCCCCCTGAAATGATTGAAGGTCGGA 82SURV NM_00116TGTTTTGATTCCCGGGCTTACCAGGTGAGAAGTGAGGGAGGAAGAAGGCAGTGTCCCTTTTGCTAGAGCTG83 ACAGCTTTG TERC U86-046AAGAGGAACGGAGCGAGTCCCCGCGCGCGGCGCGATTCCCTGAGCTGTGGGACGTGCACCCAGGACTCGGC84 TCACACAT TFRC NM_00323GCCAACTGCTTTCATTTGTGAGGGATCTGAACCAATACAGAGCAGACATAAAGGAAATGGGCCTGAGT 85TGFBR2 NM_00324AACACCAATGGGTTCCATCTTTCTGGGCTCCTGATTGCTCAAGCACAGTTTGGCCTGATGAAGAGG 86TIMP2 NM_00325TCACCCTCTGTGACTTCATCGTGCCCTGGGACACCCTGAGCACCACCCAGAAGAAGAGCCTGAACCACA 87TITF1 NM_00331CGACTCCGTTCTCAGTGTCTGACATCTTGAGTCCCCTGGAGGAAAGCTACAAGAAAGTGGGCATGGAGGG88 TP53BP1 NM_00565TGCTGTTGCTGAGTCTGTTGCCAGTCCCCAGAAGACCATGTCTGTGTTGAGCTGTATCTGTGAAGCCAGGC89 AAG upa NM_00265GTGGATGTGCCCTGAAGGACAAGCCAGGCGTCTACACGAGAGTCTCACACTTCTTACCCTGGATCCGCAG90 VEGFC NM_00542CCTCAGCAAGACGTTATTTGAAATTACAGTGCCTCTCTCTCAAGGCCCCAAACCAGTAACAATCAGTTTTG90 CCAATCACACTT XIAP NM_00116GCAGTTGGAAGACACAGGAAAGTATCCCCAAATTGCAGATTTATCAACGGCTTTTATCTTGAAAATAGTGC92 CACGCA YB-1 NM_00455AGACTGTGGAGTFTGATGTTGTTGAAGGAGAAAAGGGTGCGGAGGCAGCAAATGTTACAGGTCCTGGTGGT93 GTTCC

TABLES 6A-6F Gene Accession Name Sequence Length Seq ID. A-CateninNM_001903 S2138/A-Cate.f2 CGTTCCGATCCTCTATACTGCAT 23 94 A-CateninNM_001903 S2139/A-Cate.r2 AGGTCCCTGTTGGCCTTATAGG 22 95 A-CateninNM_001903 S4725/A-Cate.p2 ATGCCTACAGCACCCTGATGTCGCA 25 96 AKT1 NM_005163S0010/AKT1.f3 CGCTTCTATGGCGCTGAGAT 20 97 AKT1 NM_005163 S0012/AKT1.r3TCCCGGTACACCACGTTCTT 20 98 AKT1 NM_005163 S4776/AKT1.p3CAGCCCTGGACTACCTGCACTCGG 24 99 AKT2 NM_001626 S0828/AKT2.f3TCCTGCCACCCTTCAAACC 19 100 AKT2 NM_001626 S0829/AKT2.r3GGCGGTAAATTCATCATCGAA 21 101 AKT2 NM_001626 S4727/AKT2.p3CAGGTCACGTCCGAGGTCGACACA 24 102 APC NM_000038 S0022/APC.f4GGACAGCAGGAATGTGTTTC 20 103 APC NM_000038 S0024/APC.r4ACCCACTCGATTTGTTTCTG 20 104 APC NM_000038 S4888/APC.p4CATTGGCTCCCCGTGACCTGTA 22 105 B-Catenin NM_001904 S2150/B-Cate.f3GGCTCTTGTGCGTACTGTCCTT 22 106 B-Catenin NM_001904 S2151/B-Cate.r3TCAGATGACGAAGAGCACAGATG 23 107 B-Catenin NM_001904 S5046/B-Cate.p3AGGCTCAGTGATGTCTTCCCTGTCACCAG 29 108 Bak NM_001188 S0037/Bak.f2CCATTCCCACCATTCTACCT 20 109 Bak NM_001188 S0039/Bak.r2GGGAACATAGACCCACCAAT 20 110 Bak NM_001188 S4724/Bak.p2ACACCCCAGACGTCCTGGCCT 21 111 Bax NM_004324 S0040/Bax.flCCGCCGTGGACACAGACT 18 112 Bax NM_004324 S0042/Bax.r1TTGCCGTCAGAAAACATGTCA 21 113 Bax NM_004324 S4897/Bax.p1TGCCACTCGGAAAAAGACCTCTCGG 25 114 Bclx NM_001191 S0046/Bc1x.f2CTTTTGTGGAACTCTATGGGAACA 24 115 Bclx NM_001191 S0048/Bc1x.r2CAGCGGTTGAAGCGTTCCT 19 116 Bclx NM_001191 S4898/Bc1x.p2TTCGGCTCTCGGCTGCTGCA 20 117 BRAF NM_004333 S3027/BRAF.f2CCTTCCGACCAGCAGATGAA 20 118 BRAF NM_004333 S3028/BRAF.r2TTTATATGCACATTGGGAGCTGAT 24 119 BRAF NM_004333 S4818/BRAF.p2CAATTTGGGCAACGAGACCGATCCT 25 120 BRK NM_005975 S0678/BRK.f2GTGCAGGAAAGGTTCACAAA 20 121 BRK NM_005975 S0679/BRK.r2GCACACACGATGGAGTAAGG 20 122 BRK NM_005975 S4789/BRK.p2AGTGTCTGCGTCCAATACACGCGT 24 123 BTC NM_001729 S1216/BTC.f3AGGGAGATGCCGCTTCGT 18 124 BTC NM_001729 S1217/BTC.r3CTCTCACACCTTGCTCCAATGTA 23 125 BTC NM_001729 S4844/BTC.p3CCTTCATCACAGACACAGGAGGGCG 25 126 CA9 NM_001216 S1398/CA9.f3ATCCTAGCCCTGGTTTTTGG 20 127 CA9 NM_001216 S1399/CA9.r3CTGCCTTCTCATCTGCACAA 20 128 CA9 NM_001216 S4938/CA9.p3TTTGCTGTCACCAGCGTCGC 20 129 Cad17 NM_004063 S2186/Cad17.f1GAAGGCCAAGAACCGAGTCA 20 130 Cad17 NM_004063 S2187/Cad17.r1TCCCCAGTTAGTTCAAAAGTCACA 24 131 Cad17 NM_004063 S5038/Cad17.p1TTATATTCCAGTTTAAGGCCAATCCTC 27 132 CCNA2 NM_001237 S3039/CCNA2.f1CCATACCTCAAGTATTTGCCATCAG 25 133 CCNA2 NM_001237 S3040/CCNA2s1AGCTTTGTCCCGTGACTGTGTA 22 134 CCNA2 NM_001237 S4820/CCNA2.p1ATTGCTGGAGCTGCCTTTCATTTAGCACT 29 135 CCND3 NM_001760 S2799/CCND3.f1CCTCTGTGCTACAGATTATACCTTTGC 27 136 CCND3 NM_001760 S2800/CCND3.r1CACTGCAGCCCCAATGCT 18 137 CCND3 NM_001760 S4966/CCND3.p1TACCCGCCATCCATGATCGCCA 22 138 CCNE1 NM_001238 S1446/CCNE1.f1AAAGAAGATGATGACCGGGTTTAC 24 139 CCNE1 NM_001238 S1447/CCNE1.r1GAGCCTCTGGATGGTGCAAT 20 140 CCNE1 NM_001238 S4944/CCNE1.p1CAAACTCAACGTGCAAGCCTCGGA 24 141 CCNE2 NM_057749 S1458/CCNE2.f2ATGCTGTGGCTCCTTCCTAACT 22 142 CCNE2 NM_057749 S1459/CCNE2.r2ACCCAAATTGTGATATACAAAAAGGTT 27 143 CCNE2 NM_057749 S4945/CCNE2.p2TACCAAGCAACCTACATGTCAAGAAAGCCC 30 144 CD105 NM_000118 S1410/CD105.f1GCAGGTGTCAGCAAGTATGATCAG 24 145 CD105 NM_000118 S1411/CD105.r1TTTTTCCGCTGTGGTGATGA 20 146 CD105 NM_000118 S4940/CD105.p1CGACAGGATATTGACCACCGCCTCATT 27 147 CD134 NM_003327 S3138/CD134.f2GCCCAGTGCGGAGAACAG 18 148 CD134 NM_003327 S3139/CD134.r2AATCACACGCACCTGGAGAAC 21 149 CD134 NM_003327  S3241/CD134.p2CCAGCTTGATTCTCGTCTCTGCACTTAAGC 30 150 CD44E X55150 S3267/CD44E.f1ATCACCGACAGCACAGACA 19 151 CD44E X55150 S3268/CD44E.r1ACCTGTGTTTGGATTTGCAG 20 152 CD44E X55150 S4767/CD44E.p1CCCTGCTACCAATATGGACTCCAGTCA 27 153 CD44s M59040 S3102/CD44s.f1GACGAAGACAGTCCCTGGAT 20 154 CD44s M59040 S3103/CD44s.r1ACTGGGGTGGAATGTGTCTT 20 155 CD44s M59040 S4826/CD44s.p1CACCGACAGCACAGACAGAATCCC 24 156 CD44v3 AJ251595v3 S2997/CD44v3.f2CACACAAAACAGAACCAGGACT 22 157 CD44v3 AJ251595v3 S2998/CD44v3.r2CTGAAGTAGCACTTCCGGATT 21 157 CD44v3 AJ251595v3 S4814/CD44v3.p2ACCCAGTGGAACCCAAGCCATTC 23 159 CD44v6 AJ251595v6 S3003/CD44v6.f1CTCATACCAGCCATCCAATG 20 160 CD44v6 AJ251595v6 S3004/CD44v6.r1TTGGGTTGAAGAAATCAGTCC 21 161 CD44v6 AJ251595v6 S4815/CD44v6.p1CACCAAGCCCAGAGGACAGTTCCT 24 162 CD68 NM_001251 S0067/CD68.f2TGGTTCCCAGCCCTGTGT 18 163 CD68 NM_001251 S0069/CD68.r2CTCCTCCACCCTGGGTTGT 19 164 CD68 NM_001251 S4734/CD68.p2CTCCAAGCCCAGATTCAGATTCGAGTCA 28 165 CD82 NM_002231 S0684/CD82.f3GTGCAGGCTCAGGTGAAGTG 20 166 CD82 NM_002231 S0685/CD82.r3GACCTCAGGGCGATTCATGA 20 167 CD82 NM_002231 S4790/CD82.p3TCAGCTTCTACAACTGGACAGACAACGCTG 30 168 CD9 NM_001769 S0686/CD9.f1GGGCGTGGAACAGTTTATCT 20 168 CD9 NM_001769 S0687/CD9.r1CACGGTGAAGGTTTCGAGT 19 170 CD9 NM_001769 S4792/CD9.p1AGACATCTGCCCCAAGAAGGACGT 24 171 CDC25B NM_021874 S1160/CDC25B.f1AAACGAGCAGTTTGCCATCAG 21 172 CDC25B NM_021874 51161/CDC25B.r1GTTGGTGATGTTCCGAAGCA 20 176 CDC25B NM_021874 S4842/CDC25B.p1CCTCACCGGCATAGACTGGAAGCG 24 174 CEACAM6 NM_002483 S3197/CEACAM.f1CACAGCCTCACTTCTAACCTTCTG 24 175 CEACAM6 NM_002483 S3198/CEACAM.r1TTGAATGGCGTGGATTCAATAG 22 176 CEACAM6 NM_002483 S3261/CEACAM.p1ACCCACCCACCACTGCCAAGCTC 23 177 CGA NM_001275 S3221/CGA.f3CTGAAGGAGCTCCAAGACCT 20 178 CGA NM_001275 S3222/CGA.r3CAAAACCGCTGTGTTTCTTC 20 179 CGA NM_001275 S3254/CGA.p3TGCTGATGTGCCCTCTCCTTGG 22 180 Chk2 NM_007194 S1434/Chk2.f3ATGTGGAACCCCCACCTACTT 21 181 Chk2 NM_007194 S1435/Chk2.r3CAGTCCACAGCACGGTTATACC 22 182 Chk2 NM_007194 S4942/Chk2.p3AGTCCCAACAGAAACAAGAACTTCAGGCG 29 183 cMet NM_000245 S0082/cMet.f2GACATTTCCAGTCCTGCAGTCA 22 184 cMet NM_000245 S0084/cMet.r2CTCCGATCGCACACATTTGT 20 185 cMet NM_000245 S4993/cMet.p2TGCCTCTCTGCCCCACCCTTTGT 23 186 COX2 NM_000963 S0088/COX2.f1TCTGCAGAGTTGGAAGCACTCTA 23 187 COX2 NM_000963 S0090/COX2.r1GCCGAGGCTTTTCTACCAGAA 21 188 COX2 NM_000963 S4995/COX2.p1CAGGATACAGCTCCACAGCATCGATGTC 28 189 cripto NM_003212 S3117/cripto.f1 GGGTCTGTGCCCCATGAC 18 190 cripto NM_003212 S3118/cripto.r1 TGACCGTGCCAGCATTTACA 20 191 cripto NM_003212 S3237/cripto.p1 CCTGGCTGCCCAAGAAGTGTTCCCT 25 192 CTSL NM_001912 S1303/CTSL.f2GGGAGGCTTATCTCACTGAGTGA 23 193 CTSL NM_001912 S1304/CTSL.r2CCATTGCAGCCTTCATTGC 19 194 CTSL NM_001912 S4899/CTSL.p2TTGAGGCCCAGAGCAGTCTACCAGATTCT 29 195 DCR3 NM_016434 S1786/DCR3.f3GACCAAGGTCCTGGAATGTC 20 196 DCR3 NM_016434 51787/DCR3.r3GTCTTCCCTGTACCCGTAGG 20 197 DCR3 NM_016434 S4982/DCR3.p3CAGGATGCCATTCACCTTCTGCTG 24 198 DIABLO NM_019887 S0808/DIABLO.f1CACAATGGCGGCTCTGAAG 19 199 DIABLO NM_019887 S0809/DIABLO.r1ACACAAACACTGTCTGTACCTGAAGA 26 200 DIABLO NM_019887 S4813/DIABLO.p1AAGTTACGCTGCGCGACAGCCAA 23 201 DPYD NM_000110 S0100/DPYD.f2AGGACGCAAGGAGGGTTTG 19 202 DPYD NM_000110 S0102/DPYD.r2GATGTCCGCCGAGTCCTTACT 21 203 DPYD NM_000110 S4998/DPYD.p2CAGTGCCTACAGTCTCGAGTCTGCCAGTG 29 204 DR5 NM_003842 S2551/DR5.f2CTCTGAGACAGTGCTTCGATGACT 24 205 DR5 NM_003842 S2552/DR5.r2CCATGAGGCCCAACTTCCT 19 206 DR5 NM_003842 S4979/DR5.p2CAGACTTGGTGCCCTTTGACTCC 23 207 EDN1 NM_001955 S0774/EDN1 e.f1TGCCACCTGGACATCATTTG 20 208 endothelin EDN1 NM_001955 S0775/EDN1 e.r1TGGACCTAGGGCTTCCAAGTC 21 209 endothelin EDN1 NM_001955 S4806/EDN1 e.p1CACTCCCGAGCACGTTGTTCCGT 23 210 endothelin EG FR NM_005228 S0103/EGFR.f2TGTCGATGGACTTCCAGAAC 20 211 EGFR NM_005228 S0105/EGFR.r2 ATTGGGACAGCTTGGATCA 19 212 EGFR NM_005228 S4999/EGFR.p2CACCTGGGCAGCTGCCAA 18 213 EGFRd27 EGFRd27 S2484/EGFRd2.f2 GAGTCGGGCTCTGGAGGAAAAG 22 214 EGFRd27 EGFRd27 S2485/EGFRd2.r2 CCACAGGCTCGGACGCAC 18 215 EGFRd27 EGFRd27 S4935/EGFRd2.p2AGCCGTGATCTGTCACCACATAATTACC 28 216 EIF4E NM_001968 S0106/EIF4E.f1GATCTAAGATGGCGACTGTCGAA 23 217 EIF4E NM_001968  S0108/EIF4E.r1TTAGATTCCGTTTTCTCCTCTTCTG 25 218 EIF4E NM_001968 S5000/EIF4E.p1ACCACCCCTACTCCTAATCCCCCGACT 27 219 ErbB3 NM_001982 S0112/ErbB3.f1CGGTTATGTCATGCCAGATACAC 23 220 Erb B3 NM_001982 S0114/ErbB3.r1GAACTGAGACCCACTGAAGAAAGG 24 221 Erb B3 NM_001982 S5002/ErbB3.p1CCTCAAAGGTACTCCCTCCTCCCGG 25 222 ERBB4 NM_005235 S1231/ERBB4.f3TGGCTCTTAATCAGTTTCGTTACCT 25 223 ERBB4 NM_005235 S1232/ERBB4.r3CAAGGCATATCGATCCTCATAAAGT 25 224 ERBB4 NM_005235 S4891/ERBB4.p3TGTCCCACGAATAATGCGTAAATTCTCCAG 30 225 EREG NM_001432 S0670/EREG.f1ATAACAAAGTGTAGCTCTGACATGAATG 28 226 EREG NM_001432 S0671/EREG.r1CACACCTGCAGTAGTTTTGACTCA 24 227 EREG NM001432 S4772/EREG.p1TTGTTTGCATGGACAGTGCATCTATCTGGT 30 228 ERK1 Z11696 S1560/ERK1.f3ACGGATCACAGTGGAGGAAG 20 229 ERK1 Z11696 S1561/ERK1.r3CTCATCCGTCGGGTCATAGT 20 230 ERK1 Z11696 S4882/ERK1.p3CGCTGGCTCACCCCTACCTG 20 231 fas NM_000043 S0118/fas.f1GGATTGCTCAACAACCATGCT 21 232 fas NM_000043 S0120/fas.r1GGCATTAACACTTTTGGACGATAA 24 233 fas NM_000043 S5003/fas.p1TCTGGACCCTCCTACCTCTGGTTCTTACGT 30 234 FRP1 NM_003012 S1804/FRP1.f3TTGGTACCTGTGGGTTAGCA 20 235 FRP1 NM_003012 S1805/FRP1.r3CACATCCAAATGCAAACTGG 20 236 FRP1 NM_003012 S4983/FRP1.p3TCCCCAGGGTAGAATTCAATCAGAGC 26 237 GPC3 NM_004484 S1835/GPC3.f1TGATGCGCCTGGAAACAGT 19 238 GPC3 NM_004484 S1836/GPC3.r1CGAGGTTGTGAAAGGTGCTTATC 23 239 GPC3 NM_004484 S5036/GPC3.p1AGCAGGCAACTCCGAAGGACAACG 24 240 GRO1 NM_001511 S0133/GRO1.f2CGAAAAGATGCTGAACAGTGACA 23 241 GRO1 NM_001511 S0135/GRO1.r2TCAGGAACAGCCACCAGTGA 20 242 GRO1 NM_001511 S5006/GRO1.p2CTTCCTCCTCCCTTCTGGTCAGTTGGAT 28 243 GUS NM_000181 S0139/GUS.f1CCCACTCAGTAGCCAAGTCA 20 244 GUS NM_000181 S0141/GUS.r1CACGCAGGTGGTATCAGTCT 20 245 GUS NM_000181 S4740/GUS.p1TCAAGTAAACGGGCTGTTTTCCAAACA 27 246 HB-EGF NM_001945 S0662/HB-EGF.f1GACTCCTTCGTCCCCAGTTG 20 247 HB-EGF NM_001945 S0663/HB-EGF.r1TGGCACTTGAAGGCTCTGGTA 21 248 HB-EGF NM_001945 S4787/HB-EGF.p1TTGGGCCTCCCATAATTGCTTTGCC 25 249 HER2 NM_004448 S0142/HER2.f3CGGTGTGAGAAGTGCAGCAA 20 250 HER2 NM_004448 S0144/HER2.r3CCTCTCGCAAGTGCTCCAT 19 251 HER2 NM_004448 S4729/HER2.p3CCAGACCATAGCACACTCGGGCAC 24 242 HGF M29145 S1327/HGF.f4CCGAAATCCAGATGATGATG 20 253 HGF M29145 S1328/HGF.r4 CCCAAGGAATGAGTGGATTT20 254 HGF M29145 S4901/HGF.p4 CTCATGGACCCTGGTGCTACACG 23 255 ID1NM_002165 S0820/ID1.f1 AGAACCGCAAGGTGAGCAA 19 256 ID1 NM_002165S0821/ID1.r1 TCCAACTGAAGGTCCCTGATG 21 257 ID1 NM_002165 S4832/ID1.p1TGGAGATTCTCCAGCACGTCATCGAC 26 258 IGF1R NM_000875 S1249/IGF1R.f3GCATGGTAGCCGAAGATTTCA 21 259 IGF1R NM_000875 S1250/IGF1R.r3TTTCCGGTAATAGTCTGTCTCATAGATATC 30 260 IGF1R NM_000875 S4895/IGF1R.p3CGCGTCATACCAAAATCTCCGATTTTGA 28 261 IGFBP3 NM_000598 S0157/IGFBP3.f3ACGCACCGGGTGTCTGA 17 262 IGFBP3 NM_000598 S0159/IGFBP3.r3TGCCCTTTCTTGATGATGATTATC 24 263 IGFBP3 NM_000598 S5011/IGFBP3.p3CCCAAGTTCCACCCCCTCCATTCA 24 264 IRS1 NM_005544 S1943/IRS1.f3CCACAGCTCACCTTCTGTCA 20 265 IRS1 NM_005544 S1944/IRS1.r3CCTCAGTGCCAGTCTCTTCC 20 266 IRS1 NM_005544 S5050/IRS1.p3TCCATCCCAGCTCCAGCCAG 20 267 ITGA3 NM_002204 S2347/ITGA3.f2CCATGATCCTCACTCTGCTG 20 268 ITGA3 NM_002204 S2348/ITGA3.r2GAAGCTTTGTAGCCGGTGAT 20 269 ITGA3 NM_002204 S4852/ITGA3.p2CACTCCAGACCTCGCTTAGCATGG 24 270 ITGB3 NM_000212 S3126/ITGB3.f1ACCGGGAGCCCTACATGAC 19 271 ITGB3 NM_000212 S3127/ITGB3.r1CCTTAAGCTCTTTCACTGACTCAATCT 27 272 ITGB3 NM_000212 S3243/ITGB3.p1AAATACCTGCAACCGTTACTGCCGTGAC 28 273 KRT17 NM_000422 S0172/KRT17.f2CGAGGATTGGTT.CTTCAGCAA 21 274 KRT17 NM_000422 S0174/KRT17.r2ACTCTGCACCAGCTCACTGTTG 22 275 KRT17 NM_000422 S5013/KRT17.p2CACCTCGCGGTTCAGTTCCTCTGT 24 276 LAMC2 NM_005562 S2826/LAMC2.f2ACTCAAGCGGAAATTGAAGCA 21 277 LAMC2 NM_005562 S2827/LAMC2.r2ACTCCCTGAAGCCGAGACACT 21 278 LAMC2 NM_005562 S4969/LAMC2.p2AGGTCTTATCAGCACAGTCTCCGCCTCC 28 278 MTA1 NM_004689 S2369/MTA1.f1CCGCCCTCACCTGAAGAGA 19 280 MTA1 NM_004689 S2370/MTA1.r1GGAATAAGTTAGCCGCGCTTCT 22 281 MTA1 NM_004689 S4855/MTA1.p1CCCAGTGTCCGCCAAGGAGCG 21 282 NMYC NM_005378 S2884/NMYC.f2TGAGCGTCGCAGAAACCA 18 283 NMYC NM_005378 S2885/NMYC.r2TCCCTGAGCGTGAGAAAGCT 20 284 NMYC NM_005378 S4976/NMYC.p2CCAGCGCCGCAACGACCTTC 20 285 p14ARF NM_000077 S0199/p14ARF.f3GCGGAAGGTCCCTCAGACA 19 286 p14ARF NM_000077 S0201/p14ARF.r3TCTAAGTTTCCCGAGGTTTCTCA 23 287 p14ARF NM_000077 S5068/p14ARF.p3CCCCGATTGAAAGAACCAGAGAGGCT 26 288 p27 NM_004064 S0205/p27.f3CGGTGGACCACGAAGAGTTAA 21 289 p27 NM_004064 S0207/p27.r3GGCTCGCCTCTTCCATGTC 19 290 p27 NM_004064 S4750/p27.p3CCGGGACTTGGAGAAGCACTGCA 23 291 P53 NM_000546 S0208/P53.f2CTTTGAACCCTTGCTTGCAA 20 292 P53 NM_000546 S0210/P53.r2CCCGGGACAAAGCAAATG 18 293 P53 NM_000546 S5065/P53.p2AAGTCCTGGGTGCTTCTGACGCACA 25 294 PAI1 NM_000602 S0211/PAI1.f3CCGCAACGTGGTTTTCTCA 19 295 PAI1 NM_000602 S0213/PAI1.r3TGCTGGGTTTCTCCTCCTGTT 21 296 PAI1 NM_000602 S5066/PAI1.p3CTCGGTGTTGGCCATGCTCCAG 22 297 PDGFA NM_002607 S0214/PDGFA.f3TTGTTGGTGTGCCCTGGTG 19 298 PDGFA NM_002607 S0216/PDGFA.r3TGGGTTCTGTCCAAACACTGG 21 299 PDGFA NM_002607 S5067/PDGFA.p3TGGTGGCGGTCACTCCCTCTGC 22 300 PDGFB NM_002608 S0217/PDGFB.f3ACTGAAGGAGACCCTTGGAG 20 301 PDGFB NM_002608 S0219/PDGFB.r3TAAATAACCCTGCCCACACA 20 302 PDGFB NM_002608 S5014/PDGFB.p3TCTCCTGCCGATGCCCCTAGG 21 303 PGK1 NM_000291 S0232/PGK1.f1AGAGCCAGTTGCTGTAGAACTCAA 24 304 PGK1 NM_000291 S0234/PGK1.r1CTGGGCCTACACAGTCCTTCA 21 305 PGK1 NM_000291 S5022/PGK1.p1TCTCTGCTGGGCAAGGATGTTCTGTTC 27 306 PLAUR NM_002659 S1976/PLAUR.f3CCCATGGATGCTCCTCTGAA 20 307 PLAUR NM_002659 S1977/PLAUR.r3CCGGTGGCTACCAGACATTG 20 308 PLAUR NM_002659 S5054/PLAUR.p3CATTGACTGCCGAGGCCCCATG 22 309 PPARG NM_005037 S3090/PPARG.f3TGACTTTATGGAGCCCAAGTT 21 310 PPARG NM_005037 S3091/PPARG.r3GCCAAGTCGCTGTCATCTAA 20 311 PPARG NM_005037 S4824/PPARG.p3TTCCAGTGCATTGAACTTCACAGCA 25 312 PTPD1 NM_007039 S3069/PTPD1.f2CGCTTGCCTAACTCATACTTTCC 23 313 PTPD1 NM_007039 S3070/PTPD1.r2CCATTCAGACTGCGCCACTT 20 314 PTPD1 NM_007039 S4822/PTPD1.p2TCCACGCAGCGTGGCACTG 19 315 RANBP2 NM_006267 S3081/RANBP2.f3TCCTTCAGCTTTCACACTGG 20 316 RANBP2 NM_006267 S3082/RANBP2.r3AAATCCTGTTCCCACCTGAC 20 317 RANBP2 NM_006267 S4823/RANBP2.p3TCCAGAAGAGTCATGCAACTTCATTTCTG 29 318 RASSF1 NM_007182 S2393/RASSF1.f3AGTGGGAGACACCTGACCTT 20 319 RASSF1 NM_007182 S2394/RASSF1.s3TGATCTGGGCATTGTACTCC 20 320 RASSF1 NM_007182 S4909/RASSFl.p3TTGATCTTCTGCTCAATCTCAGCTTGAGA 29 321 RB1 NM_000321 S2700/RB1.f1CGAAGCCCTTACAAGTTTCC 20 322 RB1 NM_000321 S2701/RB1.r1GGACTCTTCAGGGGTGAAAT 20 323 RB1 NM_000321 S4765/RB1.p1CCCTTACGGATTCCTGGAGGGAAC 24 324 RIZ1 NM_012231 S1320/RIZ1.f2CCAGACGAGCGATTAGAAGC 20 325 RIZ1 NM_012231 S1321/RIZ1.r2TCCTCCTCTTCCTCCTCCTC 20 326 RIZ1 NM_012231 S4761/RIZ1.p2TGTGAGGTGAATGATTTGGGG GA 23 327 RPLPO NM_001002 S0256/RPLPO.f2CCATTCTATCATCAACGGGTACAA 24 328 RPLPO NM_001002 S0258/RPLPO.r2TCAGCAAGTGGGAAGGTGTAATC 23 329 RPLPO NM_001002 S4744/RPLPO.p2TCTCCACAGACAAGGCCAGGACTCG 25 330 SPRY2 NM_005842 S2985/SPRY2.f2TGTGGCAAGTGCAAATGTAA 20 331 SPRY2 NM_005842 S2986/SPRY2.r2GTCGCAGATCCAGTCTGATG 20 332 SPRY2 NM_005842 S4811/SPRY2.p2CAGAGGCCTTGGGTAGGTGCACTC 24 333 Src NM_004383 S1820/Src.f2CCTGAACATGAAGGAGCTGA 20 334 Src NM_004383 S1821/Src.r2CATCACGTCTCCGAACTCC 19 335 Src NM_004383 S5034/Src.p2TCCCGATGGTCTGCAGCAGCT 21 336 STK15 NM_003600 S0794/STK15.f2CATCTTCCAGGAGGACCACT 20 337 STK15 NM_003600 S0795/STK15.r2TCCGACCTTCAATCATTTCA 20 338 STK15 NM_003600 S4745/STK15.p2CTCTGTGGCACCCTGGACTACCTG 24 339 SURV NM_001168 S0259/SURV.f2TGTTTTGATTCCCGGGCTTA 20 340 SURV NM_001168 S0261/SURV.r2CAAAGCTGTCAGCTCTAGCAAAAG 24 341 SURV NM_001168 S4747/SURV.p2TGCCTTCTTCCTCCCTCACTTCTCACCT 28 342 TERC U86046 S2709/TERC.f2AAGAGGAACGGAGCGAGTC 19 343 TERC U86046 S2710/TERC.r2 ATGTGTGAGCCGAGTCCTG19 344 TERC U86046 S4958/TERC.p2 CACGTCCCACAGCTCAGGGAATC 23 345 TFRCNM_003234 S1352/TFRC.f3 GCCAACTGCTTTCATTTGTG 20 346 TFRC NM_003234S1353/TFRC.r3 ACTCAGGCCCATTTCCTTTA 20 347 TFRC NM_003234 S4748/TFRC.p3AGGGATCTGAACCAATACAGAGCAGACA 28 348 TGFBR2 NM_003242 S2422/TGFB R213AACACCAATGGGTTCCATCT 20 349 TGFBR2 NM_003242 S2423/TGFBR2.r3CCTCTTCATCAGGCCAAACT 20 350 TGFBR2 NM_003242 S4913/TGFBR2.p3TTCTGGGCTCCTGATTGCTCAAGC 24 351 TIMP2 NM_003255 S1680/TIMP2.f1TCACCCTCTGTGACTTCATCGT 22 352 TIMP2 NM_003255 S1681/TIMP2.r1TGTGGTTCAGGCTCTTCTTCTG 22 353 TIMP2 NM_003255 S4916/TIMP2.p1CCCTGGGACACCCTGAGCACCA 22 354 TITF1 NM_003317 S2224/TITF1.f1CGACTCCGTTCTCAGTGTCTGA 22 355 TITF1 NM_003317 S2225/TITF1.r1CCCTCCATGCCCACTTTCT 19 356 TITF1 NM_003317 S4829/TITF1.p1ATCTTGAGTCCCCTGGAGGAAAGC 24 357 TP53BP1 NM_005657 S1747/TP53BP.f2TGCTGTTGCTGAGTCTGTTG 20 358 TP53BP1 NM_005657 S1748/TP53BP.r2CTTGCCTGGCTTCACAGATA 20 359 TP53BP1 NM_005657 S4924/TP53BP.p2CCAGTCCCCAGAAGACCATGTCTG 24 360 upa NM_002658 S0283/upa.f3GTGGATGTGCCCTGAAGGA 19 361 upa NM_002658 S0285/upa.r3CTGCGGATCCAGGGTAAGAA 20 362 upa NM_002658 S4769/upa.p3AAGCCAGGCGTCTACACGAGAGTCTCAC 28 363 VEGFC NM_005429 S2251/VEGFC.f1CCTCAGCAAGACGTTATTTGAAATT 25 364 VEGFC NM_005429 S2252/VEGFC.r1AAGTGTGATTGGCAAAACTGATTG 24 365 VEGFC NM_005429 S4758/VEGFC.p1CCTCTCTCTCAAGGCCCCAAACCAGT 26 366 XIAP NM_001167 S0289/XIAP.f1GCAGTTGGAAGACACAGGAAAGT 23 367 XIAP NM_001167 S0291/XIAP.r1TGCGTGGCACTATTTTCAAGA 21 368 XIAP NM_001167 S4752/XIAP.p1TCCCCAAATTGCAGATTTATCAACGGC 27 369 YB-1 NM_004559 S1194/YB-1.f2AGACTGTGGAGTTTGATGTTGTTGA 25 370 YB-1 NM_004559 S1195/YB-1.r2GGAACACCACCAGGACCTGTAA 22 371 YB-1 NM_004559 S4843/YB-1.p2TTGCTGCCTCCGCACCCTTTTCT 23 372

1-55. (canceled)
 56. A method for predicting the likelihood that a humancolon cancer patient will exhibit a clinically beneficial patientresponse to treatment with an EGFR inhibitor, the method comprising: a)assaying a normalized level of an RNA transcript in a sample comprisingEGFR-expressing colon cancer cells obtained from said patient, whereinthe RNA transcript is the transcript of KRT17; b) analyzing thenormalized level of the KRT17 RNA transcript; and c) predicting thelikelihood of response of the patient to treatment with the EGFRinhibitor, wherein an increased normalized level of the KRT17 RNAtranscript correlates with a decreased likelihood of response totreatment with the EGFR inhibitor.
 57. The method of claim 56, whereinsaid sample is a tissue sample.
 58. The method of claim 57, wherein thetissue sample is fixed, paraffin-embedded, fresh, or frozen.
 59. Themethod of claim 57, wherein the tissue sample is derived from fineneedle, core, or other types of biopsy.
 60. The method of claim 56,wherein the EGFR inhibitor is an anti-EGFR monoclonal antibody.
 61. Themethod of claim 60, wherein the anti-EGFR monoclonal antibody iscetuximab.
 62. The method of claim 56, wherein the EGFR inhibitor is asmall molecule tyrosine-kinase inhibitor.
 63. The method of claim 62,wherein the small molecule tyrosine kinase inhibitor is gefitinib orerlotinib.
 64. The method of claim 56, further comprising the step ofpreparing a report comprising a prediction of the likelihood that thepatient will respond to treatment with the EGFR inhibitor.
 65. Themethod of claim 56, wherein the normalized level of the KRT17 RNAtranscript is determined using reverse transcription polymerase chainreaction (RT-PCR).
 66. The method of claim 56, wherein the normalizedlevel of the KRT17 RNA transcript is determined using an arraycomprising polynucleotides hybridizing to a KRT17 gene immobilized on asolid surface.
 67. The method of claim 56, wherein RNA is isolated fromcolon cancer cells present in a fixed, paraffin-embedded tissue by aprocedure comprising: (a) incubating one or more sections of said fixed,paraffin-embedded tissue at a temperature of about 56° C. to 70° C. in alysis buffer, in the presence of a protease, without prior dewaxing, toform a lysis solution; (b) cooling the lysis solution to a temperaturewhere the paraffin solidifies, thereby generating a cooled lysissolution; and (c) isolating the RNA from said cooled lysis solution.